From d704db996dfc26abf2da0706189e4d454928dd26 Mon Sep 17 00:00:00 2001
From: Jon Froehlich <jonf@cs.uw.edu>
Date: Tue, 18 Aug 2026 06:41:13 -0700
Subject: [PATCH 1/7] One challenger registry, and freeze the witness pool the
 #46 pass was made under (#122)
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`CHALLENGERS`, `SPARSE` and `DENSE` were three tuples kept in step by hand, and
`silent_witness.py` iterated the roster directly with no way to point it anywhere
else. That made adding a model to the benchmark quietly expensive in the one place
nobody would look: a finished human pass.

`rampnet/roster.py` is now the single table. It carries each model's spec, label,
density class, the date it joined, and whether it is scored in the roster tables;
`CHALLENGERS`, `SPARSE`, `DENSE` and the per-provider defaults all derive from it.

The load-bearing part is `WITNESS_POOL_46`, written out literally rather than
derived, and it is `silent_witness.py`'s new `--models` default. The hazard is not
hypothetical — measured here:

  frozen pool (7 models)   59 unwitnessed, sparse-union excess +39.0
  plus gemini-3.7-flash    58 unwitnessed, sparse-union excess +35.6

The one item that drops out is morgantown:356422300574178 at (0.09899, 0.54838).
It is one of the 50 crops already tagged, and it carries one of only two
`definition` verdicts in the whole pass. Adding an already-published leg to the
roster would have orphaned it, changed the gallery's manifest digest, and moved the
published lower bound from 0.0092 to 0.0088 recall points, with nothing raising a
hand. Now a new challenger moves the comparison tables and leaves the human pass
alone by construction.

Also:

- `silent_witness.py` takes `--models`, and derives its sparse/dense split from the
  pool it was given. An unregistered or unmeasured model now raises instead of being
  silently filed as dense, which is what `spec in SPARSE else "DENSE"` did.
- The "union of the 5 sparse models" / "2 dense detectors" strings read their counts
  off the pool instead of having them baked in.
- Both `silent_witness.json` and `fp_taxonomy.json` record the pool they ran over,
  so a verdict file can be matched to the pool that produced its items — the same
  reasoning as the detector signature inside each published detections file.
- gemini-3.7-flash is registered as published-but-off-roster (#120). Its density is
  measured, not assumed: 1.90 boxes/pano over 2,109 panos, against gemini-3.6-flash's
  2.34 and OWLv2's 72.77.

Both committed artifacts regenerate with the `models` block as the only diff: every
number is unchanged, and `unwitnessed` is identical in content and order.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
---
 analysis_out/fp_taxonomy.json      |  35 ++++
 analysis_out/silent_witness.json   |  32 ++++
 rampnet/roster.py                  | 246 +++++++++++++++++++++++++++++
 scripts/analysis/fp_taxonomy.py    |  57 +++----
 scripts/analysis/silent_witness.py |  65 +++++---
 5 files changed, 379 insertions(+), 56 deletions(-)
 create mode 100644 rampnet/roster.py

diff --git a/analysis_out/fp_taxonomy.json b/analysis_out/fp_taxonomy.json
index bacd66aa..b1f6b05f 100644
--- a/analysis_out/fp_taxonomy.json
+++ b/analysis_out/fp_taxonomy.json
@@ -10,6 +10,41 @@
     "paterson",
     "gainesville"
   ],
+  "models": {
+    "pool": null,
+    "specs": [
+      "rampnet",
+      "gemini:gemini-3.6-flash",
+      "gemini:gemini-3.1-pro-preview",
+      "qwen:Qwen/Qwen3-VL-8B-Instruct",
+      "qwen:Qwen/Qwen3-VL-32B-Instruct",
+      "molmo:allenai/Molmo2-8B",
+      "owlv2",
+      "gdino"
+    ],
+    "labels": [
+      "rampnet",
+      "gemini-3.6-flash",
+      "gemini-3.1-pro-preview",
+      "Qwen/Qwen3-VL-8B-Instruct",
+      "Qwen/Qwen3-VL-32B-Instruct",
+      "allenai/Molmo2-8B",
+      "google/owlv2-large-patch14-ensemble",
+      "IDEA-Research/grounding-dino-base"
+    ],
+    "sparse": [
+      "rampnet",
+      "gemini:gemini-3.6-flash",
+      "gemini:gemini-3.1-pro-preview",
+      "qwen:Qwen/Qwen3-VL-8B-Instruct",
+      "qwen:Qwen/Qwen3-VL-32B-Instruct",
+      "molmo:allenai/Molmo2-8B"
+    ],
+    "dense": [
+      "owlv2",
+      "gdino"
+    ]
+  },
   "per_model": {
     "rampnet @0.30": {
       "n_fp": 181,
diff --git a/analysis_out/silent_witness.json b/analysis_out/silent_witness.json
index af72774f..8d1dab7a 100644
--- a/analysis_out/silent_witness.json
+++ b/analysis_out/silent_witness.json
@@ -2,6 +2,38 @@
   "bucket": "silent",
   "threshold": 0.3,
   "n": 128,
+  "models": {
+    "pool": "WITNESS_POOL_46",
+    "specs": [
+      "gemini:gemini-3.6-flash",
+      "gemini:gemini-3.1-pro-preview",
+      "qwen:Qwen/Qwen3-VL-8B-Instruct",
+      "qwen:Qwen/Qwen3-VL-32B-Instruct",
+      "molmo:allenai/Molmo2-8B",
+      "owlv2",
+      "gdino"
+    ],
+    "labels": [
+      "gemini-3.6-flash",
+      "gemini-3.1-pro-preview",
+      "Qwen/Qwen3-VL-8B-Instruct",
+      "Qwen/Qwen3-VL-32B-Instruct",
+      "allenai/Molmo2-8B",
+      "google/owlv2-large-patch14-ensemble",
+      "IDEA-Research/grounding-dino-base"
+    ],
+    "sparse": [
+      "gemini:gemini-3.6-flash",
+      "gemini:gemini-3.1-pro-preview",
+      "qwen:Qwen/Qwen3-VL-8B-Instruct",
+      "qwen:Qwen/Qwen3-VL-32B-Instruct",
+      "molmo:allenai/Molmo2-8B"
+    ],
+    "dense": [
+      "owlv2",
+      "gdino"
+    ]
+  },
   "per_model": {
     "gemini-3.6-flash": {
       "witnessed": 33,
diff --git a/rampnet/roster.py b/rampnet/roster.py
new file mode 100644
index 00000000..5a7e9ec2
--- /dev/null
+++ b/rampnet/roster.py
@@ -0,0 +1,246 @@
+"""The challenger roster: who is in the model comparison, since when, and how dense.
+
+One table, ``ROSTER``, replaces three tuples that used to be kept in step by hand —
+``CHALLENGERS``, ``SPARSE`` and ``DENSE`` — plus the per-provider default model ids
+that were copied into four argument parsers. Adding a model to the benchmark is now
+one entry here.
+
+**Why this lives in the package rather than in an analysis script.** Both
+``scripts/analysis/*`` and ``scripts/model_comparison/*`` need it, it must import
+without torch so a fresh clone can score published detections on a laptop, and the
+CPU-only test suite has to cover it. It follows the splits registry in
+``scripts/analysis/miss_decomposition.py``, which eight scripts already import.
+
+**The one thing in here that must not move: ``WITNESS_POOL_46``.** It is written out
+literally rather than derived from ``ROSTER`` precisely so that adding a challenger
+cannot touch it. See the comment on it.
+
+Three properties of an entry are worth stating because they are easy to get wrong:
+
+* ``density`` is **evidence, not configuration** — it comes from the measured
+  boxes-per-panorama in ``docs/model_comparison.md`` (sparse models emit 1-4, the
+  open-vocabulary detectors 55-88). A new arm's density is unknown until it has been
+  run, so it is ``None``, and ``density_of`` raises rather than guessing. The old code
+  silently treated an unclassified model as dense.
+* ``standing`` separates *scored in the roster tables* from *published but not scored*.
+  A leg can be run, verified and committed long before its write-up lands
+  (``gemini-3.7-flash``, #120); that is an omission of a write-up, not of a run, and
+  the distinction is data here rather than prose in a doc.
+* ``label`` is the resolved model id used for result-table rows and for
+  ``benchmark/model_detections/<label>__<city>.json``. For nearly every provider it is
+  derivable from the spec; ``LABEL_OVERRIDES`` covers the ones where it is not.
+"""
+from collections import namedtuple
+
+#: One registered model. ``spec`` is the ``compare.py --models`` token.
+Challenger = namedtuple(
+    "Challenger", "spec label provider density standing added note")
+
+# --------------------------------------------------------------------------- #
+# The registry
+# --------------------------------------------------------------------------- #
+#: Every model the benchmark knows about, scored or not, in results-table order.
+#:
+#: ``rampnet`` is a member: it is the row every other row is read against, and having
+#: it here is what makes "8 models" and "7 challengers" the same statement rather than
+#: the contradiction that sat in docs/model_comparison.md and docs/replication.md.
+ROSTER = (
+    Challenger(
+        spec="rampnet", label="rampnet", provider="rampnet",
+        density="sparse", standing=True, added="2026-07-22",
+        note="The subject, not a challenger. Read from the bundle's records.jsonl at "
+             "the deployed threshold, not from .model_cache — it carries no detector "
+             "signature. 4.2 boxes/pano."),
+    Challenger(
+        spec="gemini:gemini-3.6-flash", label="gemini-3.6-flash", provider="gemini",
+        density="sparse", standing=True, added="2026-07-22",
+        note="Hosted chat VLM, boxes without scores, so one operating point."),
+    Challenger(
+        spec="gemini:gemini-3.1-pro-preview", label="gemini-3.1-pro-preview",
+        provider="gemini", density="sparse", standing=True, added="2026-07-22",
+        note="Strongest general model on most splits until claude-opus-5 (#122)."),
+    Challenger(
+        spec="qwen:Qwen/Qwen3-VL-8B-Instruct", label="Qwen/Qwen3-VL-8B-Instruct",
+        provider="qwen", density="sparse", standing=True, added="2026-07-22",
+        note="Open-weight chat VLM. Outranks its own 32B on four splits — the "
+             "benchmark's only ranking inversion; see the 32B-caution mechanism."),
+    Challenger(
+        spec="qwen:Qwen/Qwen3-VL-32B-Instruct", label="Qwen/Qwen3-VL-32B-Instruct",
+        provider="qwen", density="sparse", standing=True, added="2026-07-22",
+        note="Scaling flipped the failure mode instead of fixing it: it stops firing."),
+    Challenger(
+        spec="molmo:allenai/Molmo2-8B", label="allenai/Molmo2-8B", provider="molmo",
+        density="sparse", standing=True, added="2026-07-23",
+        note="Points rather than boxes — RampNet's native output format, so no "
+             "box-to-point reduction. Needs its own env at transformers==4.57.1."),
+    Challenger(
+        spec="owlv2", label="google/owlv2-large-patch14-ensemble", provider="owlv2",
+        density="dense", standing=True, added="2026-07-22",
+        note="Open-vocabulary detector with calibrated scores, so a real PR curve. "
+             "55-88 boxes/pano: most of its recall is what the match radius hands out "
+             "for free, hence the chance corrections everywhere."),
+    Challenger(
+        spec="gdino", label="IDEA-Research/grounding-dino-base", provider="gdino",
+        density="dense", standing=True, added="2026-07-22",
+        note="Open-vocabulary detector, scored boxes. Dense for the same reason."),
+
+    # --- published, but not scored in the roster tables ---------------------- #
+    Challenger(
+        spec="gemini:gemini-3.7-flash", label="gemini-3.7-flash", provider="gemini",
+        density="sparse", standing=False, added="2026-08-14",
+        note="Run on all ten splits and published (#120); held out of the scored "
+             "tables until its write-up lands, so every table is one consistent set. "
+             "Promoting it is this entry's `standing` field plus a re-run of "
+             "fp_taxonomy/null_recall — the #46 human pass is no longer affected. "
+             "Density measured 2026-08-18 off the published detections: 1.90 "
+             "boxes/pano over 2,109 panos, against gemini-3.6-flash's 2.34 and "
+             "OWLv2's 72.77."),
+)
+
+#: Specs whose label cannot be derived from the spec, because the ``model_id`` slot
+#: carries something other than a model id. Empty until an arm needs it.
+LABEL_OVERRIDES = {}
+
+# --------------------------------------------------------------------------- #
+# The frozen pool — read the comment before touching it
+# --------------------------------------------------------------------------- #
+#: The witness pool the #46 human tagging pass was made under, as it stood on
+#: 2026-07-31. This is ``silent_witness.py``'s default.
+#:
+#: **Frozen deliberately, and written out literally rather than derived from
+#: ``ROSTER``.** ``silent_witness`` computes the RampNet misses that no other model
+#: witnessed; a further witness can only shrink that set. The set is the item list for
+#: the #46 tagging pass, which is finished, with committed per-rater verdicts at
+#: ``benchmark/miss_taxonomy_46/silent__jonf.json`` (50 items, manifest digest
+#: ``360b5ddf8751dcd0``). Verdicts are meaningless against a list other than the one
+#: they were made on, and the breakage would be silent — the numbers would simply
+#: change. So a new challenger moves the comparison tables and leaves the human pass
+#: alone, by construction rather than by anyone remembering.
+#:
+#: To run a different pool, pass ``--models``. Do not edit this to add a model.
+WITNESS_POOL_46 = (
+    "gemini:gemini-3.6-flash",
+    "gemini:gemini-3.1-pro-preview",
+    "qwen:Qwen/Qwen3-VL-8B-Instruct",
+    "qwen:Qwen/Qwen3-VL-32B-Instruct",
+    "molmo:allenai/Molmo2-8B",
+    "owlv2",
+    "gdino",
+)
+
+# --------------------------------------------------------------------------- #
+# Per-provider defaults — one definition, consumed by every parser
+# --------------------------------------------------------------------------- #
+#: Defaults for every ``compare.py`` argument that feeds ``build_detector`` and so
+#: the detection signature and cache key. ``compare.py``'s parser, ``fp_taxonomy``'s
+#: ``_compare_args`` shim, ``null_recall.py`` and ``dump_detections.py`` all read
+#: these, so they cannot drift apart: a wrong default here does not crash, it changes
+#: the cache key and every lookup silently misses.
+PROVIDER_DEFAULTS = {
+    "gemini_model": "gemini-3.6-flash",
+    "claude_model": "claude-sonnet-5",
+    "claude_effort": "low",
+    "claude_tool_choice": "auto",
+    # As-run encoding/decoding for the published Claude legs. ``None`` is what keeps
+    # them OUT of the detection signature (a setting enters it only when it deviates
+    # from as-run), so changing either default here silently rebuilds a different
+    # cache key and every lookup misses.
+    "claude_image_format": None,
+    "claude_temperature": None,
+    "qwen_model": "Qwen/Qwen3-VL-8B-Instruct",
+    "qwen_coord_space": "auto",
+    "owlv2_model": "google/owlv2-large-patch14-ensemble",
+    "gdino_model": "IDEA-Research/grounding-dino-base",
+    "molmo_model": "allenai/Molmo2-8B",
+    "molmo_coord_scale": "auto",
+    "yolo_conf": 0.05,
+    "yolo_iou": 0.5,
+    "yolo_imgsz": 1024,
+}
+
+# --------------------------------------------------------------------------- #
+# Derived views — nothing below is hand-maintained
+# --------------------------------------------------------------------------- #
+BY_SPEC = {c.spec: c for c in ROSTER}
+
+#: Standing entries, RampNet included — the set every results table scores.
+SCORED = tuple(c for c in ROSTER if c.standing)
+
+#: Standing challengers, i.e. everything scored except RampNet itself.
+CHALLENGERS = tuple(c.spec for c in SCORED if c.provider != "rampnet")
+
+#: What ``fp_taxonomy.py --models`` defaults to: RampNet plus the challengers.
+SCORED_SPECS = tuple(c.spec for c in SCORED)
+
+#: Published and verified, but not scored in the roster tables.
+OFF_ROSTER = tuple(c for c in ROSTER if not c.standing)
+
+#: Sparse enough that a hit is evidence rather than coverage.
+SPARSE = tuple(s for s in CHALLENGERS if BY_SPEC[s].density == "sparse")
+
+#: So dense that a hit is mostly coverage; reported, never used for a headline.
+DENSE = tuple(s for s in CHALLENGERS if BY_SPEC[s].density == "dense")
+
+
+def label_for(spec, cargs=None):
+    """The table row / filename label a ``--models`` spec resolves to.
+
+    ``cargs`` is an optional namespace of provider defaults (``compare.py``'s parsed
+    args, or ``fp_taxonomy._compare_args``). It is consulted so that a run with
+    ``--gemini-model`` overridden labels itself with the model actually used rather
+    than with the registry's default.
+    """
+    if spec in LABEL_OVERRIDES:
+        return LABEL_OVERRIDES[spec]
+    provider, _, model_id = spec.partition(":")
+    provider, model_id = provider.strip(), model_id.strip()
+    if model_id:
+        return model_id
+    key = f"{provider}_model"
+    if cargs is not None and getattr(cargs, key, None):
+        return getattr(cargs, key)
+    return PROVIDER_DEFAULTS.get(key, provider)
+
+
+def density_of(spec):
+    """``"sparse"`` or ``"dense"`` for a registered spec.
+
+    Raises for anything unregistered or unmeasured. That is the point: density is
+    measured boxes-per-panorama, not a setting, and the previous code silently
+    treated an unknown model as dense — which would quietly move a headline, since
+    only the sparse union feeds one.
+    """
+    entry = BY_SPEC.get(spec)
+    if entry is None:
+        raise KeyError(
+            f"{spec!r} is not in the roster (rampnet/roster.py). Add an entry, or "
+            f"pass a pool that excludes it.")
+    if entry.density is None:
+        raise ValueError(
+            f"{spec!r} has no measured density yet, so it cannot join a witness pool: "
+            f"a witness count is only meaningful against that model's own box rate. "
+            f"Run it, read boxes/pano off null_recall.py, then set `density`.")
+    return entry.density
+
+
+def partition_by_density(specs):
+    """``(sparse, dense)`` for an arbitrary pool, in the pool's own order."""
+    sparse = tuple(s for s in specs if density_of(s) == "sparse")
+    dense = tuple(s for s in specs if density_of(s) == "dense")
+    return sparse, dense
+
+
+def pool_record(specs, cargs=None):
+    """A JSON-able description of a model pool, to embed in an analysis artifact.
+
+    Every published detections file already carries the detector ``signature`` that
+    produced it; an analysis whose *item list* depends on which models ran needs the
+    same treatment, or a verdict file can no longer be matched to the pool that
+    generated its items.
+    """
+    specs = tuple(specs)
+    sparse, dense = partition_by_density(specs)
+    named = "WITNESS_POOL_46" if specs == WITNESS_POOL_46 else None
+    return {"pool": named, "specs": list(specs),
+            "labels": [label_for(s, cargs) for s in specs],
+            "sparse": list(sparse), "dense": list(dense)}
diff --git a/scripts/analysis/fp_taxonomy.py b/scripts/analysis/fp_taxonomy.py
index 80724753..73bffc0c 100644
--- a/scripts/analysis/fp_taxonomy.py
+++ b/scripts/analysis/fp_taxonomy.py
@@ -56,25 +56,19 @@
 sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
 sys.path.insert(0, os.path.join(REPO, "scripts", "model_comparison"))
 
+from rampnet import roster  # noqa: E402
 from rampnet.detection_eval import (  # noqa: E402
     PANO_SCALE_X, PANO_SCALE_Y, prediction_confidence, radius_sq_for)
 from rampnet.metrics import greedy_match  # noqa: E402
 
 from miss_decomposition import HELD_OUT, TIER, US_SPLITS  # noqa: E402
 
-# The roster from docs/model_comparison.md's class table. RampNet is read from the
-# committed records.jsonl (it has no cache signature); the rest come from
-# .model_cache. Defaults here must match compare.py's, or the signature — and so the
-# cache key — changes and every lookup misses.
-CHALLENGERS = (
-    "gemini:gemini-3.6-flash",
-    "gemini:gemini-3.1-pro-preview",
-    "qwen:Qwen/Qwen3-VL-8B-Instruct",
-    "qwen:Qwen/Qwen3-VL-32B-Instruct",
-    "molmo:allenai/Molmo2-8B",
-    "owlv2",
-    "gdino",
-)
+# The roster now lives in rampnet/roster.py — one table that also carries each
+# model's density class, the date it joined, and whether it is scored in the roster
+# tables. Re-exported here because three analysis scripts already import it from this
+# module. RampNet is read from the committed records.jsonl (it has no cache
+# signature); the challengers come from .model_cache.
+CHALLENGERS = roster.CHALLENGERS
 
 # Where the ego vehicle starts. Set from the data, not assumed: across the seven
 # pooled splits the 99.5th percentile of ground-truth ramp height is y=0.725 and the
@@ -186,29 +180,21 @@ def summarize_fp(rows):
 def _compare_args(cache_dir):
     """A namespace matching ``compare.py``'s parser defaults.
 
-    Every field here feeds ``build_detector`` and therefore the cache signature. It
-    is spelled out rather than imported because ``compare.main`` builds its parser
-    inline; ``test_fp_taxonomy.py`` asserts these still match the parser's defaults
-    so a drift in compare.py fails a test instead of silently missing every cache
-    entry and reporting zero detections.
+    Every field here feeds ``build_detector`` and therefore the cache signature. The
+    per-provider model ids come from ``rampnet.roster.PROVIDER_DEFAULTS`` so there is
+    one definition rather than a copy per parser; the rest are compare.py's own
+    non-provider defaults, which still have to be restated because ``compare.main``
+    builds its parser inline. ``test_fp_taxonomy.py`` asserts the whole namespace
+    still matches that parser, so a drift in compare.py fails a test instead of
+    silently missing every cache entry and reporting zero detections.
     """
     import argparse as _a
     ns = _a.Namespace()
     for k, v in dict(
-            gemini_model="gemini-3.6-flash",
-            claude_model="claude-sonnet-5", claude_effort="low", claude_tool_choice="auto",
-            # As-run encoding/decoding for the published Claude legs. None/"jpeg"
-            # keep them OUT of the cache signature, so these defaults must match
-            # compare.py's or an export rebuilds a different key and finds no cache.
-            claude_image_format=None, claude_temperature=None,
-            qwen_model="Qwen/Qwen3-VL-8B-Instruct",
-            qwen_coord_space="auto",
-            owlv2_model="google/owlv2-large-patch14-ensemble",
-            gdino_model="IDEA-Research/grounding-dino-base",
-            molmo_model="allenai/Molmo2-8B", owlv2_query=None, gdino_query=None,
+            roster.PROVIDER_DEFAULTS,
+            owlv2_query=None, gdino_query=None,
             gdino_text_threshold=None, score_threshold=None,
-            molmo_coord_scale="auto", yolo_model=None, yolo_conf=0.05,
-            yolo_iou=0.5, yolo_imgsz=1024, tiling="perspective",
+            yolo_model=None, tiling="perspective",
             radius=0.022, op_threshold=0.0, limit=None,
             cache_dir=cache_dir, no_cache=False).items():
         setattr(ns, k, v)
@@ -343,7 +329,7 @@ def gt_height_stats(cities):
 
 def main(argv=None):
     p = argparse.ArgumentParser(description=__doc__.split("\n")[0])
-    p.add_argument("--models", default=",".join(("rampnet",) + CHALLENGERS),
+    p.add_argument("--models", default=",".join(roster.SCORED_SPECS),
                    help="Comma-separated compare.py model specs. 'rampnet' is read "
                         "from analysis_out/op_cache at the deployed threshold, not "
                         "from .model_cache (it carries no detector signature).")
@@ -443,7 +429,12 @@ def main(argv=None):
         os.makedirs(os.path.dirname(os.path.abspath(args.json_out)), exist_ok=True)
         with open(args.json_out, "w", encoding="utf-8") as fh:
             json.dump({"hood_y": args.hood_y, "annulus_factor": ANNULUS_FACTOR,
-                       "cities": cities, "per_model": per_model}, fh, indent=2)
+                       "cities": cities,
+                       # Which models this ran over, so a reader can tell a roster
+                       # change from a numbers change -- the same reasoning as the
+                       # detector signature inside each published detections file.
+                       "models": roster.pool_record(specs, cargs),
+                       "per_model": per_model}, fh, indent=2)
         print(f"\nWrote {args.json_out}")
     return 0
 
diff --git a/scripts/analysis/silent_witness.py b/scripts/analysis/silent_witness.py
index 67bacf0a..a6222eac 100644
--- a/scripts/analysis/silent_witness.py
+++ b/scripts/analysis/silent_witness.py
@@ -45,22 +45,22 @@
 sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
 sys.path.insert(0, os.path.join(REPO, "scripts", "model_comparison"))
 
+from rampnet import roster  # noqa: E402
 from rampnet.detection_eval import PANO_SCALE_X, PANO_SCALE_Y, radius_sq_for  # noqa: E402
 
 import miss_taxonomy as mt  # noqa: E402
 from miss_decomposition import US_SPLITS  # noqa: E402
 from fp_taxonomy import CHALLENGERS, _compare_args, scaled  # noqa: E402
 
-# Models sparse enough that a hit is evidence rather than coverage. Assigned from the
-# measured densities in docs/model_comparison.md (1-4 boxes/pano, nulls 0.01-0.08)
-# versus the open detectors' 55-88. The split is not a judgement call at the boundary:
-# there is an order of magnitude between the two groups. Both are reported; only the
-# sparse group is used for the headline, and the dense group's excess is printed so
-# that choice is checkable rather than asserted.
-SPARSE = ("gemini:gemini-3.6-flash", "gemini:gemini-3.1-pro-preview",
-          "qwen:Qwen/Qwen3-VL-8B-Instruct", "qwen:Qwen/Qwen3-VL-32B-Instruct",
-          "molmo:allenai/Molmo2-8B")
-DENSE = ("owlv2", "gdino")
+# Sparse = a hit is evidence; dense = a hit is mostly coverage. Both come from the
+# measured densities in docs/model_comparison.md (1-4 boxes/pano at nulls 0.01-0.08,
+# versus the open detectors' 55-88), and the classification lives with the model in
+# rampnet/roster.py rather than in a second tuple here that had to be hand-synced.
+# The split is not a judgement call at the boundary: there is an order of magnitude
+# between the groups. Both are reported; only the sparse group feeds the headline, and
+# the dense group's excess is printed so that choice is checkable rather than asserted.
+SPARSE = roster.SPARSE
+DENSE = roster.DENSE
 
 
 # --------------------------------------------------------------------------- #
@@ -167,10 +167,22 @@ def main(argv=None):
     p.add_argument("--bucket", default="silent", choices=list(mt.BUCKETS))
     p.add_argument("--threshold", type=float, default=mt.DEFAULT_THRESHOLD)
     p.add_argument("--cities", default=",".join(US_SPLITS))
+    p.add_argument("--models", default=",".join(roster.WITNESS_POOL_46),
+                   help="Comma-separated compare.py model specs to use as witnesses. "
+                        "Defaults to roster.WITNESS_POOL_46, the pool the #46 human "
+                        "tagging pass was made under, which is frozen: a new "
+                        "challenger can only shrink the unwitnessed set, and that set "
+                        "is the item list the committed verdicts were made against. "
+                        "Pass a pool here to vary it; do not edit the frozen tuple.")
     p.add_argument("--cache-dir", default=os.path.join(REPO, ".model_cache"))
     p.add_argument("--json-out", default=None)
     args = p.parse_args(argv)
 
+    pool = tuple(m.strip() for m in args.models.split(",") if m.strip())
+    # Raises on an unregistered or unmeasured model rather than silently filing it as
+    # dense, which is what the old `spec in SPARSE else "DENSE"` did.
+    pool_sparse, pool_dense = roster.partition_by_density(pool)
+
     import compare as C
     cache = C.DetectionCache(args.cache_dir, enabled=True)
     cargs = _compare_args(args.cache_dir)
@@ -193,7 +205,7 @@ def main(argv=None):
     # Every model's predictions, once per city.
     preds = {}
     labels = {}
-    for spec in CHALLENGERS:
+    for spec in pool:
         for city in cities:
             label, got = model_predictions(city, spec, cache, cargs)
             labels[spec] = label
@@ -203,7 +215,7 @@ def main(argv=None):
     records = []
     for t in targets:
         by_model = {}
-        for spec in CHALLENGERS:
+        for spec in pool:
             pano_preds = preds.get((spec, t["city"]), {}).get(t["pano"])
             if pano_preds is None:
                 continue
@@ -217,19 +229,19 @@ def main(argv=None):
     print(f"=== Who else saw the '{args.bucket}' misses? "
           f"({n} misses, threshold {args.threshold}) ===\n")
     print(f"{'model':>42} {'witnessed':>10} {'by chance':>10} {'excess':>9} {'':>6}")
-    all_s = summarize(records, CHALLENGERS)
-    for spec in CHALLENGERS:
+    all_s = summarize(records, pool)
+    for spec in pool:
         s = all_s[spec]
-        tag = "sparse" if spec in SPARSE else "DENSE"
+        tag = "sparse" if spec in pool_sparse else "DENSE"
         print(f"{labels.get(spec, spec):>42} {s['witnessed']:>10} "
               f"{s['expected']:>10.1f} {s['excess']:>+9.1f} {tag:>6}")
 
-    sparse_s = summarize(records, SPARSE)["__union__"]
-    dense_s = summarize(records, DENSE)["__union__"]
+    sparse_s = summarize(records, pool_sparse)["__union__"]
+    dense_s = summarize(records, pool_dense)["__union__"]
     print(f"\n{'-'*82}")
-    print(f"{'union of the 5 sparse models':>42} {sparse_s['witnessed']:>10} "
+    print(f"{f'union of the {len(pool_sparse)} sparse models':>42} {sparse_s['witnessed']:>10} "
           f"{sparse_s['expected']:>10.1f} {sparse_s['excess']:>+9.1f}")
-    print(f"{'union of the 2 dense detectors':>42} {dense_s['witnessed']:>10} "
+    print(f"{f'union of the {len(pool_dense)} dense detectors':>42} {dense_s['witnessed']:>10} "
           f"{dense_s['expected']:>10.1f} {dense_s['excess']:>+9.1f}")
     print(f"{'-'*82}")
 
@@ -252,7 +264,7 @@ def main(argv=None):
         sel = [r for r in records if r["field"] == f]
         if not sel:
             continue
-        s = summarize(sel, SPARSE)["__union__"]
+        s = summarize(sel, pool_sparse)["__union__"]
         by_field[f] = s
         print(f"\n  {f}-field: {s['witnessed']}/{len(sel)} raw "
               f"({s['witnessed']/len(sel):.1%}), chance {s['expected']:.1f}, "
@@ -283,8 +295,15 @@ def main(argv=None):
         os.makedirs(os.path.dirname(os.path.abspath(args.json_out)), exist_ok=True)
         with open(args.json_out, "w", encoding="utf-8") as fh:
             json.dump({"bucket": args.bucket, "threshold": args.threshold,
-                       "n": n, "per_model": {labels.get(k, k): v
-                                             for k, v in all_s.items()},
+                       "n": n,
+                       # Which models produced this, so any verdict file can be
+                       # matched to the pool that generated its item list. Same
+                       # reasoning as the detector signature inside each published
+                       # detections file: an artifact that does not say what made
+                       # it cannot be checked, only trusted.
+                       "models": roster.pool_record(pool, cargs),
+                       "per_model": {labels.get(k, k): v
+                                     for k, v in all_s.items()},
                        "sparse_union": sparse_s, "dense_union": dense_s,
                        "by_field": by_field,
                        "unwitnessed": [
@@ -292,7 +311,7 @@ def main(argv=None):
                             "y": r["y"], "field": r["field"]}
                            for r in records
                            if not any(r["by_model"].get(m, (False, 0))[0]
-                                      for m in SPARSE)]}, fh, indent=2)
+                                      for m in pool_sparse)]}, fh, indent=2)
         print(f"\nWrote {args.json_out}")
     return 0
 

From 44cacadfc36e7ecbaa8ccb7938423832d133fe99 Mon Sep 17 00:00:00 2001
From: Jon Froehlich <jonf@cs.uw.edu>
Date: Tue, 18 Aug 2026 06:46:05 -0700
Subject: [PATCH 2/7] Read the per-provider defaults from the registry too, in
 all four parsers (#122)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

`--gemini-model`, `--qwen-model`, `--owlv2-model`, `--gdino-model`, `--molmo-model`
and the three Claude flags were written out four times: compare.py's parser,
fp_taxonomy's `_compare_args` shim, null_recall.py and dump_detections.py. They all
feed `build_detector` and therefore the detection signature and the cache key, so a
copy that drifts does not crash — it changes the key, misses every already-paid
cached detection, and reports a model with zero detections.

They now all read `roster.PROVIDER_DEFAULTS`. `null_recall.DEFAULT_MODELS` was a
fifth private copy of the roster itself; it is `roster.SCORED_SPECS` now, and it
gains the Claude flags it was missing.

`export_model_cache.spec_label` delegates to `roster.label_for`, which is the same
torch-free resolution plus a hook for providers whose `model_id` slot is not a model
id. Verified unchanged: 68/68 published (model, split) pairs still score identically
to the cache.

The AST drift guard in test_fp_taxonomy.py now resolves `_D["key"]` subscripts
against the registry rather than skipping them. Resolving instead of skipping is the
point — it keeps the provider flags inside the check, and it fails if compare.py
ever stops reading the registry.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
---
 scripts/analysis/export_model_cache.py      |  12 +-
 scripts/analysis/null_recall.py             |  31 +--
 scripts/model_comparison/compare.py         |  39 ++--
 scripts/model_comparison/dump_detections.py |  25 ++-
 tests/test_fp_taxonomy.py                   |  18 +-
 tests/test_roster.py                        | 200 ++++++++++++++++++++
 6 files changed, 281 insertions(+), 44 deletions(-)
 create mode 100644 tests/test_roster.py

diff --git a/scripts/analysis/export_model_cache.py b/scripts/analysis/export_model_cache.py
index 353088dc..eb2a4c54 100644
--- a/scripts/analysis/export_model_cache.py
+++ b/scripts/analysis/export_model_cache.py
@@ -50,6 +50,8 @@
 sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
 sys.path.insert(0, os.path.join(REPO, "scripts", "model_comparison"))
 
+from rampnet import roster  # noqa: E402
+
 from fp_taxonomy import CHALLENGERS, _compare_args  # noqa: E402
 from miss_decomposition import ALL_SPLITS  # noqa: E402
 
@@ -67,13 +69,11 @@ def spec_label(spec, cargs):
     ``build_detector`` would give the same answer, but it imports the detector stack
     (torch, transformers). The whole point of publishing the detections is that a
     fresh clone can score them with neither, so the published path must not drag that
-    import in. Provider defaults come from ``_compare_args``, which a test already
-    cross-checks against ``compare.py``'s parser, so this cannot drift on its own.
+    import in. ``roster.label_for`` is that torch-free resolution, shared with every
+    other caller; ``cargs`` is still consulted so a run with an overridden provider
+    model labels itself with the model actually used.
     """
-    provider, _, model_id = spec.partition(":")
-    if model_id.strip():
-        return model_id.strip()
-    return getattr(cargs, f"{provider.strip()}_model", provider.strip())
+    return roster.label_for(spec, cargs)
 
 
 def load_detections(label, city, published_dir=PUBLISHED_DIR, publish_as=None):
diff --git a/scripts/analysis/null_recall.py b/scripts/analysis/null_recall.py
index 0af3ba63..ee8a5587 100644
--- a/scripts/analysis/null_recall.py
+++ b/scripts/analysis/null_recall.py
@@ -69,16 +69,16 @@
 sys.path.insert(0, str(REPO_ROOT))
 sys.path.insert(0, str(REPO_ROOT / "scripts" / "model_comparison"))
 
+from rampnet import roster  # noqa: E402
 from rampnet.detection_eval import (  # noqa: E402
     aggregate, radius_sq_for, score_pano, PANO_RADIUS_NORMALIZED,
 )
 import compare  # noqa: E402
 from detectors import build_detector, parse_model_spec  # noqa: E402
 
-# The full roster the city splits are scored on, in the results-table order.
-DEFAULT_MODELS = ("rampnet,gemini:gemini-3.1-pro-preview,gemini:gemini-3.6-flash,"
-                  "molmo:allenai/Molmo2-8B,qwen:Qwen/Qwen3-VL-32B-Instruct,"
-                  "qwen:Qwen/Qwen3-VL-8B-Instruct,owlv2,gdino")
+# The full roster the city splits are scored on, from rampnet/roster.py rather than
+# a fourth private copy of it.
+DEFAULT_MODELS = ",".join(roster.SCORED_SPECS)
 
 
 def null_recall(scored, radius_sq):
@@ -122,14 +122,23 @@ def main():
                          "and a stray GPU/API call here is never what you wanted.")
     # build_detector reads these off the namespace; the defaults must match
     # compare.py's or the detector signature -- and so the cache key -- changes.
+    # rampnet.roster.PROVIDER_DEFAULTS is where they are defined, once.
+    _D = roster.PROVIDER_DEFAULTS
     ap.add_argument("--tiling", choices=["perspective", "none"], default="perspective")
-    ap.add_argument("--gemini-model", default="gemini-3.6-flash")
-    ap.add_argument("--qwen-model", default="Qwen/Qwen3-VL-8B-Instruct")
-    ap.add_argument("--qwen-coord-space", choices=["auto", "norm1000", "pixels"], default="auto")
-    ap.add_argument("--owlv2-model", default="google/owlv2-large-patch14-ensemble")
-    ap.add_argument("--gdino-model", default="IDEA-Research/grounding-dino-base")
-    ap.add_argument("--molmo-model", default="allenai/Molmo2-8B")
-    ap.add_argument("--molmo-coord-scale", choices=["auto", "100", "1000"], default="auto")
+    ap.add_argument("--gemini-model", default=_D["gemini_model"])
+    ap.add_argument("--claude-model", default=_D["claude_model"])
+    ap.add_argument("--claude-effort", default=_D["claude_effort"],
+                    choices=["low", "medium", "high", "xhigh", "max"])
+    ap.add_argument("--claude-tool-choice", default=_D["claude_tool_choice"],
+                    choices=["auto", "forced"])
+    ap.add_argument("--qwen-model", default=_D["qwen_model"])
+    ap.add_argument("--qwen-coord-space", choices=["auto", "norm1000", "pixels"],
+                    default=_D["qwen_coord_space"])
+    ap.add_argument("--owlv2-model", default=_D["owlv2_model"])
+    ap.add_argument("--gdino-model", default=_D["gdino_model"])
+    ap.add_argument("--molmo-model", default=_D["molmo_model"])
+    ap.add_argument("--molmo-coord-scale", choices=["auto", "100", "1000"],
+                    default=_D["molmo_coord_scale"])
     args = ap.parse_args()
 
     records, verdicts, panos_dir = compare.load_bundle(args.bundle)
diff --git a/scripts/model_comparison/compare.py b/scripts/model_comparison/compare.py
index 25db42a6..39b6d244 100644
--- a/scripts/model_comparison/compare.py
+++ b/scripts/model_comparison/compare.py
@@ -38,6 +38,7 @@
 sys.path.insert(0, str(REPO_ROOT))          # rampnet.* (editable install fallback)
 sys.path.insert(0, str(Path(__file__).resolve().parent))  # local detectors.py
 
+from rampnet import roster  # noqa: E402
 from rampnet.detection_eval import (  # noqa: E402
     build_ground_truth, load_yolo_ground_truths, score_pano, aggregate,
     prediction_confidence, radius_sq_for, PANO_RADIUS_NORMALIZED,
@@ -536,42 +537,49 @@ def main():
     ap.add_argument("bundle", help="Bundle dir (e.g. benchmark/richmond) with records.jsonl + verdicts.json.")
     ap.add_argument("--models", default="rampnet",
                     help=MODELS_HELP)
-    ap.add_argument("--gemini-model", default="gemini-3.6-flash")
-    ap.add_argument("--claude-model", default="claude-sonnet-5",
+    # Every provider default below comes from rampnet.roster.PROVIDER_DEFAULTS. They
+    # feed build_detector and so the detection signature and cache key, and used to
+    # be copied into four separate parsers; a copy that drifts does not crash, it
+    # changes the cache key and silently misses every already-paid detection.
+    _D = roster.PROVIDER_DEFAULTS
+    ap.add_argument("--gemini-model", default=_D["gemini_model"])
+    ap.add_argument("--claude-model", default=_D["claude_model"],
                     help="Claude model id, served via Vertex + ADC (same credentials "
                          "as the Gemini legs). Each model must be enabled separately "
                          "in Vertex Model Garden.")
-    ap.add_argument("--claude-effort", default="low",
+    ap.add_argument("--claude-effort", default=_D["claude_effort"],
                     choices=["low", "medium", "high", "xhigh", "max"],
                     help="How much Claude thinks. Thinking bills as OUTPUT and is the "
                          "dominant cost term, so this is the main cost lever; it is "
                          "part of the detection cache key. Default 'low' — reading a "
                          "view and emitting a box list is not intelligence-sensitive.")
-    ap.add_argument("--claude-tool-choice", default="auto", choices=["auto", "forced"],
+    ap.add_argument("--claude-tool-choice", default=_D["claude_tool_choice"],
+                    choices=["auto", "forced"],
                     help="'forced' guarantees the answer arrives as a tool call, but "
                          "SUPPRESSES THINKING, which makes --claude-effort inert. "
                          "'auto' (default) lets effort actually do something. Also "
                          "part of the cache key.")
-    ap.add_argument("--claude-image-format", default=None, choices=["jpeg", "png"],
+    ap.add_argument("--claude-image-format", default=_D["claude_image_format"], choices=["jpeg", "png"],
                     help="How each view is encoded before it is sent. Default 'jpeg' "
                          "(q90) is what the published annapolis legs ran; 'png' is "
                          "lossless and matches what the Gemini leg receives, so it "
                          "removes an input asymmetry between the two paid legs. "
                          "Costs no extra tokens, but it IS a cache-key change: "
                          "switching means re-paying for the detections.")
-    ap.add_argument("--claude-temperature", type=float, default=None,
+    ap.add_argument("--claude-temperature", type=float, default=_D["claude_temperature"],
                     help="Sampling temperature. Default: send none and take the "
                          "provider default, which is what the published legs did. "
                          "Pass 0.0 to match GeminiDetector's greedy decoding. Also "
                          "a cache-key change.")
-    ap.add_argument("--qwen-model", default="Qwen/Qwen3-VL-8B-Instruct")
-    ap.add_argument("--qwen-coord-space", choices=["auto", "norm1000", "pixels"], default="auto",
+    ap.add_argument("--qwen-model", default=_D["qwen_model"])
+    ap.add_argument("--qwen-coord-space", choices=["auto", "norm1000", "pixels"],
+                    default=_D["qwen_coord_space"],
                     help="Box convention the Qwen checkpoint emits: 'norm1000' (Qwen3-VL, "
                          "0-1000) or 'pixels' (Qwen2/2.5-VL, absolute). 'auto' infers it "
                          "from the model id.")
-    ap.add_argument("--owlv2-model", default="google/owlv2-large-patch14-ensemble")
-    ap.add_argument("--gdino-model", default="IDEA-Research/grounding-dino-base")
-    ap.add_argument("--molmo-model", default="allenai/Molmo2-8B")
+    ap.add_argument("--owlv2-model", default=_D["owlv2_model"])
+    ap.add_argument("--gdino-model", default=_D["gdino_model"])
+    ap.add_argument("--molmo-model", default=_D["molmo_model"])
     ap.add_argument("--owlv2-query", help=f"OWLv2 text query (default {OWLV2_QUERY!r}).")
     ap.add_argument("--gdino-query", help=f"Grounding DINO category text (default {GDINO_QUERY!r}); "
                                           "lowercase, period-terminated.")
@@ -582,21 +590,22 @@ def main():
                          "0.05. This is a CACHE floor, not the operating point: it is part of "
                          "the detector signature, so lowering it re-runs the model, while every "
                          "higher operating point is a free re-score (--op-threshold, --sweep).")
-    ap.add_argument("--molmo-coord-scale", choices=["auto", "100", "1000"], default="auto",
+    ap.add_argument("--molmo-coord-scale", choices=["auto", "100", "1000"],
+                    default=_D["molmo_coord_scale"],
                     help="Divisor for Molmo point coordinates: Molmo 1 emits percentages "
                          "(100), Molmo 2 emits 0-1000. 'auto' infers it from the tag syntax.")
     ap.add_argument("--yolo-model",
                     help="Trained YOLO weights (.pt) for the 'yolo' provider — the supervised "
                          "baseline (issue #51). Required for --models yolo; e.g. "
                          "runs/detect/train/weights/best.pt. Also settable as 'yolo:<path>'.")
-    ap.add_argument("--yolo-conf", type=float, default=0.05,
+    ap.add_argument("--yolo-conf", type=float, default=_D["yolo_conf"],
                     help="Score floor for YOLO boxes (default 0.05). Like --score-threshold for "
                          "the open-vocab detectors, this is a CACHE floor in the signature, not "
                          "the operating point; higher points are free re-scores (--op-threshold, "
                          "--sweep).")
-    ap.add_argument("--yolo-iou", type=float, default=0.5,
+    ap.add_argument("--yolo-iou", type=float, default=_D["yolo_iou"],
                     help="YOLO NMS IoU threshold (default 0.5).")
-    ap.add_argument("--yolo-imgsz", type=int, default=1024,
+    ap.add_argument("--yolo-imgsz", type=int, default=_D["yolo_imgsz"],
                     help="YOLO inference image size (default 1024, matching the perspective view "
                          "size). For --tiling none, set this to the pano-geometry training size.")
     ap.add_argument("--tiling", choices=["perspective", "none"], default="perspective",
diff --git a/scripts/model_comparison/dump_detections.py b/scripts/model_comparison/dump_detections.py
index 0ea4f8dc..0b7610a0 100644
--- a/scripts/model_comparison/dump_detections.py
+++ b/scripts/model_comparison/dump_detections.py
@@ -34,6 +34,7 @@
 sys.path.insert(0, str(REPO_ROOT))
 sys.path.insert(0, str(Path(__file__).resolve().parent))
 
+from rampnet import roster  # noqa: E402
 from equirect_tiling import (  # noqa: E402
     default_views, equirect_to_perspective, equirect_point_to_perspective)
 from detectors import build_detector, load_pano_image, parse_model_spec  # noqa: E402
@@ -150,17 +151,21 @@ def main():
     ap.add_argument("--pano", help="Pano id (default: first reviewed pano with an image).")
     ap.add_argument("--out", default="view_dump/detections", help="Output directory.")
     ap.add_argument("--source-max-edge", type=int, default=4096)
-    # Consumed by build_detector.
-    ap.add_argument("--gemini-model", default="gemini-3.6-flash")
-    ap.add_argument("--claude-model", default="claude-sonnet-5")
-    ap.add_argument("--claude-effort", default="low",
+    # Consumed by build_detector. Defaults from rampnet.roster.PROVIDER_DEFAULTS, so
+    # this overlay reproduces exactly what compare.py cached rather than a near-miss.
+    _D = roster.PROVIDER_DEFAULTS
+    ap.add_argument("--gemini-model", default=_D["gemini_model"])
+    ap.add_argument("--claude-model", default=_D["claude_model"])
+    ap.add_argument("--claude-effort", default=_D["claude_effort"],
                     choices=["low", "medium", "high", "xhigh", "max"])
-    ap.add_argument("--claude-tool-choice", default="auto", choices=["auto", "forced"])
-    ap.add_argument("--qwen-model", default="Qwen/Qwen3-VL-8B-Instruct")
-    ap.add_argument("--qwen-coord-space", choices=["auto", "norm1000", "pixels"], default="auto")
-    ap.add_argument("--owlv2-model", default="google/owlv2-large-patch14-ensemble")
-    ap.add_argument("--gdino-model", default="IDEA-Research/grounding-dino-base")
-    ap.add_argument("--molmo-model", default="allenai/Molmo2-8B")
+    ap.add_argument("--claude-tool-choice", default=_D["claude_tool_choice"],
+                    choices=["auto", "forced"])
+    ap.add_argument("--qwen-model", default=_D["qwen_model"])
+    ap.add_argument("--qwen-coord-space", choices=["auto", "norm1000", "pixels"],
+                    default=_D["qwen_coord_space"])
+    ap.add_argument("--owlv2-model", default=_D["owlv2_model"])
+    ap.add_argument("--gdino-model", default=_D["gdino_model"])
+    ap.add_argument("--molmo-model", default=_D["molmo_model"])
     ap.add_argument("--owlv2-query")
     ap.add_argument("--gdino-query")
     ap.add_argument("--gdino-text-threshold", type=float)
diff --git a/tests/test_fp_taxonomy.py b/tests/test_fp_taxonomy.py
index c5fcc60b..4aad4546 100644
--- a/tests/test_fp_taxonomy.py
+++ b/tests/test_fp_taxonomy.py
@@ -24,6 +24,7 @@
 sys.path.insert(0, os.path.join(REPO, "scripts", "analysis"))
 
 import fp_taxonomy as fx  # noqa: E402
+from rampnet import roster  # noqa: E402
 from rampnet.detection_eval import PANO_SCALE_X, PANO_SCALE_Y, radius_sq_for  # noqa: E402
 
 RSQ = radius_sq_for()
@@ -193,10 +194,16 @@ def test_empty_model_does_not_divide_by_zero():
 # drift guard — the silent failure mode
 # --------------------------------------------------------------------------- #
 def _compare_parser_defaults():
-    """``{dest: default}`` for every literal-defaulted flag in compare.py.
+    """``{dest: default}`` for every statically-resolvable flag default in compare.py.
 
     Parsed from the source with ``ast`` rather than by importing: compare.py builds
     its parser inside ``main`` and pulls in the detector stack, which needs torch.
+
+    Two default shapes resolve. A plain literal, and ``_D["key"]`` — the per-provider
+    defaults, which since #122 come from ``rampnet.roster.PROVIDER_DEFAULTS`` instead
+    of being spelled out here. Resolving the subscript rather than skipping it is the
+    point: it keeps this drift check covering the provider flags, and it fails if
+    compare.py ever stops reading the registry.
     """
     path = os.path.join(REPO, "scripts", "model_comparison", "compare.py")
     with open(path, encoding="utf-8") as fh:
@@ -214,8 +221,15 @@ def _compare_parser_defaults():
             continue
         dest = long[2:].replace("-", "_")
         for kw in node.keywords:
-            if kw.arg == "default" and isinstance(kw.value, ast.Constant):
+            if kw.arg != "default":
+                continue
+            if isinstance(kw.value, ast.Constant):
                 out[dest] = kw.value.value
+            elif (isinstance(kw.value, ast.Subscript)
+                    and isinstance(kw.value.value, ast.Name)
+                    and kw.value.value.id == "_D"
+                    and isinstance(kw.value.slice, ast.Constant)):
+                out[dest] = roster.PROVIDER_DEFAULTS[kw.value.slice.value]
     return out
 
 
diff --git a/tests/test_roster.py b/tests/test_roster.py
new file mode 100644
index 00000000..b7ad162b
--- /dev/null
+++ b/tests/test_roster.py
@@ -0,0 +1,200 @@
+"""The challenger registry (#122): its invariants, and the freeze it exists to hold.
+
+The tests that matter here are the ones about ``WITNESS_POOL_46``. Everything else
+in this file is ordinary consistency checking; those are a guard on a finished human
+pass, and the failure they prevent is silent — the numbers simply change.
+"""
+import json
+import pathlib
+
+import pytest
+
+from rampnet import roster
+
+REPO = pathlib.Path(__file__).resolve().parents[1]
+
+
+# --------------------------------------------------------------------------- #
+# The freeze
+# --------------------------------------------------------------------------- #
+def test_the_46_witness_pool_is_exactly_what_the_human_pass_ran_against():
+    """The #46 tagging verdicts are only meaningful against the item list that
+    produced them, and that list is a function of this pool. It is written out
+    literally in roster.py rather than derived, so that adding a challenger cannot
+    move it; this pins the literal."""
+    assert roster.WITNESS_POOL_46 == (
+        "gemini:gemini-3.6-flash",
+        "gemini:gemini-3.1-pro-preview",
+        "qwen:Qwen/Qwen3-VL-8B-Instruct",
+        "qwen:Qwen/Qwen3-VL-32B-Instruct",
+        "molmo:allenai/Molmo2-8B",
+        "owlv2",
+        "gdino",
+    )
+
+
+def test_the_witness_pool_is_not_derived_from_the_standing_roster():
+    """The point of the freeze is that these two can diverge. They happen to be
+    equal today; a test that asserted equality would re-create exactly the coupling
+    #122 removed, so assert the weaker, permanent property instead."""
+    assert set(roster.WITNESS_POOL_46) <= {c.spec for c in roster.ROSTER}
+
+
+def test_the_committed_silent_witness_artifact_records_the_frozen_pool():
+    """An analysis whose item list depends on which models ran has to say which
+    models ran, or a verdict file cannot be matched to the pool that made its items."""
+    data = json.loads((REPO / "analysis_out" / "silent_witness.json").read_text("utf-8"))
+    assert data["models"]["pool"] == "WITNESS_POOL_46"
+    assert tuple(data["models"]["specs"]) == roster.WITNESS_POOL_46
+
+
+def test_the_committed_verdicts_still_match_the_gallery_they_were_made_on():
+    """The end of the chain the freeze protects: 50 tagged items, one manifest
+    digest. If a roster change ever reaches this, these stop agreeing."""
+    base = REPO / "benchmark" / "miss_taxonomy_46"
+    verdicts = json.loads((base / "silent__jonf.json").read_text("utf-8"))
+    manifest = json.loads((base / "silent_gallery" / "manifest.json").read_text("utf-8"))
+    assert verdicts["manifest_digest"] == manifest["digest"]
+    assert verdicts["n_items"] == verdicts["n_tagged"] == manifest["n"] == 50
+    assert set(verdicts["verdicts"]) == set(manifest["items"])
+
+
+# --------------------------------------------------------------------------- #
+# Registry consistency
+# --------------------------------------------------------------------------- #
+def test_specs_and_labels_are_unique():
+    specs = [c.spec for c in roster.ROSTER]
+    labels = [c.label for c in roster.ROSTER]
+    assert len(specs) == len(set(specs))
+    # Labels are filenames in benchmark/model_detections; a collision would have two
+    # models overwriting each other's published detections.
+    assert len(labels) == len(set(labels))
+
+
+def test_every_entry_label_is_what_label_for_resolves():
+    """`label` is data used to render the docs table; `label_for` is what the export
+    path actually calls. They must not be two answers to one question."""
+    for c in roster.ROSTER:
+        assert roster.label_for(c.spec) == c.label, c.spec
+
+
+def test_challengers_are_the_standing_roster_without_rampnet():
+    assert "rampnet" not in roster.CHALLENGERS
+    assert roster.SCORED_SPECS == ("rampnet",) + roster.CHALLENGERS
+    assert all(roster.BY_SPEC[s].standing for s in roster.CHALLENGERS)
+
+
+def test_sparse_and_dense_partition_the_standing_challengers():
+    assert set(roster.SPARSE) | set(roster.DENSE) == set(roster.CHALLENGERS)
+    assert not set(roster.SPARSE) & set(roster.DENSE)
+
+
+def test_the_open_vocabulary_detectors_are_the_dense_ones():
+    """Density is measured boxes/pano, not a preference: the open-vocab detectors sit
+    at 55-88 against everything else's 1-4."""
+    assert set(roster.DENSE) == {"owlv2", "gdino"}
+
+
+def test_off_roster_entries_are_published_but_not_scored():
+    assert roster.OFF_ROSTER, "gemini-3.7-flash should be registered (#120)"
+    for c in roster.OFF_ROSTER:
+        assert not c.standing
+        assert c.spec not in roster.SCORED_SPECS
+
+
+def test_every_entry_records_when_it_joined():
+    for c in roster.ROSTER:
+        assert c.added and len(c.added) == 10, c.spec
+        assert c.note, c.spec
+
+
+# --------------------------------------------------------------------------- #
+# density_of / partition_by_density refuse to guess
+# --------------------------------------------------------------------------- #
+def test_density_of_rejects_an_unregistered_model():
+    with pytest.raises(KeyError):
+        roster.density_of("gemini:not-a-real-model")
+
+
+def test_density_of_rejects_an_unmeasured_model():
+    """The old code filed anything outside SPARSE as dense, silently. Only the sparse
+    union feeds a headline, so a wrong guess here moves a published number."""
+    unmeasured = roster.Challenger(
+        spec="vistas:curb-cut", label="x", provider="vistas", density=None,
+        standing=False, added="2026-08-18", note="n/a")
+    saved = dict(roster.BY_SPEC)
+    roster.BY_SPEC[unmeasured.spec] = unmeasured
+    try:
+        with pytest.raises(ValueError):
+            roster.density_of(unmeasured.spec)
+    finally:
+        roster.BY_SPEC.clear()
+        roster.BY_SPEC.update(saved)
+
+
+def test_partition_by_density_keeps_the_pools_own_order():
+    pool = ("gdino", "gemini:gemini-3.6-flash", "owlv2", "molmo:allenai/Molmo2-8B")
+    sparse, dense = roster.partition_by_density(pool)
+    assert sparse == ("gemini:gemini-3.6-flash", "molmo:allenai/Molmo2-8B")
+    assert dense == ("gdino", "owlv2")
+
+
+# --------------------------------------------------------------------------- #
+# pool_record — the provenance block embedded in analysis artifacts
+# --------------------------------------------------------------------------- #
+def test_pool_record_names_the_frozen_pool_only_when_it_is_that_pool():
+    assert roster.pool_record(roster.WITNESS_POOL_46)["pool"] == "WITNESS_POOL_46"
+    # Same members, different order: not the same pool, because the pool is a
+    # sequence and the artifact must not claim provenance it does not have.
+    shuffled = tuple(reversed(roster.WITNESS_POOL_46))
+    assert roster.pool_record(shuffled)["pool"] is None
+    assert roster.pool_record(roster.WITNESS_POOL_46 + ("gemini:gemini-3.7-flash",))["pool"] is None
+
+
+def test_pool_record_is_json_serializable_and_complete():
+    rec = roster.pool_record(roster.WITNESS_POOL_46)
+    json.dumps(rec)
+    assert set(rec) == {"pool", "specs", "labels", "sparse", "dense"}
+    assert len(rec["labels"]) == len(rec["specs"])
+    assert len(rec["sparse"]) + len(rec["dense"]) == len(rec["specs"])
+
+
+# --------------------------------------------------------------------------- #
+# label_for's override path and the cargs override
+# --------------------------------------------------------------------------- #
+def test_label_for_follows_an_overridden_provider_model():
+    """A run with --gemini-model set must publish under the model actually used, not
+    under the registry default, or its detections land in the wrong file."""
+    class _Args:
+        gemini_model = "gemini-2.5-flash"
+    assert roster.label_for("gemini", _Args()) == "gemini-2.5-flash"
+    # An explicit model id in the spec still wins over the namespace.
+    assert roster.label_for("gemini:gemini-3.6-flash", _Args()) == "gemini-3.6-flash"
+
+
+def test_label_overrides_win_for_providers_whose_model_id_slot_is_not_a_model():
+    saved = dict(roster.LABEL_OVERRIDES)
+    roster.LABEL_OVERRIDES["vistas:curb-cut"] = "mask2former-vistas-curb-cut"
+    try:
+        assert roster.label_for("vistas:curb-cut") == "mask2former-vistas-curb-cut"
+    finally:
+        roster.LABEL_OVERRIDES.clear()
+        roster.LABEL_OVERRIDES.update(saved)
+
+
+# --------------------------------------------------------------------------- #
+# The registry vs. the parsers that consume it
+# --------------------------------------------------------------------------- #
+def test_provider_defaults_match_compare_pys_parser():
+    """The defaults feed build_detector and so the cache key. A drift does not crash;
+    it silently misses every already-paid cached detection."""
+    import sys
+    sys.path.insert(0, str(REPO / "scripts" / "model_comparison"))
+    import compare  # noqa: E402
+
+    parser = compare.build_parser() if hasattr(compare, "build_parser") else None
+    if parser is None:
+        pytest.skip("compare.py builds its parser inline inside main()")
+    defaults = {a.dest: a.default for a in parser._actions}
+    for key, value in roster.PROVIDER_DEFAULTS.items():
+        assert defaults[key] == value, key

From 3735f9268ddd631e858300d93251f6364180eb9b Mon Sep 17 00:00:00 2001
From: Jon Froehlich <jonf@cs.uw.edu>
Date: Tue, 18 Aug 2026 06:51:01 -0700
Subject: [PATCH 3/7] Say what the roster is by deriving it, not by counting it
 in prose (#122)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

The roster count was written by hand in four documents, and two of them disagreed:
docs/model_comparison.md said "all 8" in ten coverage-matrix cells while
docs/replication.md said "seven-model roster" — both true, about different things,
neither saying so — with a ninth leg published in the repo at the time.

docs/model_comparison.md now carries a table generated by `python -m rampnet.roster`,
and `tests/test_roster.py` fails if the doc and the registry disagree. The matrix
cells say "full roster" rather than a number. The stale-phrase guard collapses
whitespace before checking, because every one of these was wrapped across a line
break and a naive substring check finds none of them.

Four errors fixed in passages this touched anyway:

- curb_ramp_data_sourcing.md said the #46 reviewer pass was not done. It was
  completed and committed on 2026-07-31 — 50/50 tagged, digest 360b5ddf8751dcd0,
  `visible` 41 / `unclear` 4 / `context-only` 3 / `definition` 2.
- its verdict table listed six of the eight verdicts, silently dropping
  `context-only` and `definition` — the two that most affect what the `visible` rate
  means, and both actually used in the pass.
- replication.md pointed at benchmark/miss_taxonomy_46/silent__manifest.json, which
  does not exist; the digest is in silent_gallery/manifest.json.
- replication.md said `--verify` skips "nine files"; there are ten.

The bracket section now states which pool it is against, and says plainly that
adding gemini-3.7-flash would move it from 0.0092 to 0.0088 and drop an
already-rated item. scripts/analysis/README.md stops restating the bracket at all —
it is a function of the pool, so it belongs next to the pool, not in a script index.

The point estimate is still not computed, deliberately: it needs a decision about
whether `context-only` and `definition` count toward the sourcing target, and it
rests on one rater with no agreement statistic (#46, #74).

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
---
 docs/curb_ramp_data_sourcing.md | 46 ++++++++++++++++-------
 docs/model_comparison.md        | 66 ++++++++++++++++++++-------------
 docs/replication.md             | 28 +++++++++-----
 rampnet/roster.py               | 27 ++++++++++++++
 scripts/analysis/README.md      |  5 ++-
 tests/test_roster.py            | 42 +++++++++++++++++++++
 6 files changed, 164 insertions(+), 50 deletions(-)

diff --git a/docs/curb_ramp_data_sourcing.md b/docs/curb_ramp_data_sourcing.md
index 9ad9702b..9f6f723c 100644
--- a/docs/curb_ramp_data_sourcing.md
+++ b/docs/curb_ramp_data_sourcing.md
@@ -258,6 +258,14 @@ human, and exactly what more training data targets.
 The density correction is mandatory here, for the third time in this analysis: OWLv2 witnesses
 121 of 128 silent misses, but chance alone accounts for 76.9 of them.
 
+**Every number in this section is against one fixed witness pool** —
+`rampnet.roster.WITNESS_POOL_46`, the roster as it stood on 2026-07-31, which is the pool the
+#46 tagging pass below was rated under. The pool is frozen and `silent_witness.json` records
+it, because a further witness can only shrink the unwitnessed set and that set is the pass's
+item list. This is not hypothetical: adding the already-published `gemini-3.7-flash` leg takes
+the unwitnessed count from 59 to 58 and the lower bound from 0.0092 to 0.0088, and the item it
+removes is one of the 50 already rated. See #122.
+
 | witness | raw | by chance | **excess** |
 | :--- | ---: | ---: | ---: |
 | gemini-3.1-pro-preview | 46 | 9.4 | +36.6 |
@@ -265,8 +273,8 @@ The density correction is mandatory here, for the third time in this analysis: O
 | molmo2-8B | 26 | 8.5 | +17.5 |
 | Qwen3-VL-8B | 22 | 6.1 | +15.9 |
 | Qwen3-VL-32B | 16 | 2.7 | +13.3 |
-| **union, 5 sparse models** | **69** | 30.0 | **+39.0** |
-| *union, 2 dense detectors* | *127* | *102.2* | *+24.8* |
+| **union, the pool's sparse models** | **69** | 30.0 | **+39.0** |
+| *union, the pool's dense detectors* | *127* | *102.2* | *+24.8* |
 
 **Near-field: 32 of 45 witnessed raw (71.1%), chance 13.0, so ~19 corrected (42%).**
 
@@ -287,8 +295,9 @@ what the gallery is for.
 
 - **`silent` is still an upper bound**, now with a floor under it. It means the cached detections
   witness nothing there. Occlusion, deep shadow, debris and GT disagreement all still live inside
-  the unwitnessed remainder, and separating them needs the imagery — that is #46's gallery half,
-  **the crops are built but the reviewer pass is not done**.
+  the unwitnessed remainder, and separating them needs the imagery — that is #46's gallery half.
+  **One rater has now done that pass** (`benchmark/miss_taxonomy_46/silent__jonf.json`, 50/50
+  tagged, committed 2026-07-31); no second rater has, so there is no agreement statistic.
 - **The witness test is one-directional.** A witnessed ramp is confirmed recognizable; an
   unwitnessed one is not confirmed *un*recognizable, since every challenger is weaker than RampNet
   on this task and may simply have missed it too.
@@ -308,19 +317,28 @@ python scripts/analysis/make_tagger.py analysis_out/gallery46_silent
 
 That yields **50 crops** — 59 unwitnessed, less 9 below the 30-source-pixel floor, which are
 excluded from any rate rather than labelled. The verdict scheme is built so exactly one answer is
-sourcing-addressable:
+sourcing-addressable. It has eight verdicts, and the authoritative copy — the one that travels
+inside every per-rater file — is `benchmark/RUBRICS.md` §3:
 
 | verdict | what it means | programme |
 | :--- | :--- | :--- |
-| `visible` | clear ramp, unobstructed | **vocabulary — this is the sourcing target** |
-| `occluded` | vehicle, pole, vegetation, person | capture |
-| `lighting` | deep shadow or blown highlight | capture |
-| `surface` | debris, snow, leaves, construction | environment |
-| `not-a-ramp` | no ramp / flush or blended transition | GT disagreement |
-| `unclear` | cannot tell from this imagery | excluded from every rate |
-
-**The `visible` rate over those 50, applied to the 59, is what converts the bracket into a point
-estimate.** Until it is run, quote the bracket.
+| `visible` | the ramp itself is resolvable | **vocabulary — this is the sourcing target** |
+| `context-only` | ramp not resolvable; crosswalk / apron / curb-cut cues imply one | learnable, from scene layout |
+| `occluded` | something physically in the way (even if still identifiable) | capture |
+| `lighting` | exposure **destroyed** it — clipped white or crushed black | capture |
+| `surface` | debris, snow, leaves, construction covering it | environment |
+| `not-a-ramp` | nothing ramp-like here | GT error |
+| `definition` | imagery clear; whether this **class** counts is the question | rubric question |
+| `unclear` | cannot tell even with context | excluded from every rate |
+
+**One rater has completed this pass** — `benchmark/miss_taxonomy_46/silent__jonf.json`, 50/50
+tagged against manifest digest `360b5ddf8751dcd0`, committed 2026-07-31: `visible` 41,
+`unclear` 4, `context-only` 3, `definition` 2.
+
+**The bracket is still what to quote.** Converting those verdicts into a point estimate needs a
+decision this document does not get to make on its own — whether `context-only` and `definition`
+count toward the sourcing target — and it rests on a single rater with no agreement statistic
+(#74, #46). Both are open.
 - **Some of `merged` may be double-marked GT.** 24 of 124 pairs sit below 8 px (~25 cm at 10 m),
   which is not a physical spacing for two ramps; on the verdict splits that is plausibly one ramp
   marked twice. If so they are *spurious GT* and leave the population entirely rather than changing
diff --git a/docs/model_comparison.md b/docs/model_comparison.md
index b5a0aae5..81078bb9 100644
--- a/docs/model_comparison.md
+++ b/docs/model_comparison.md
@@ -13,29 +13,45 @@ a run that hasn't happened, not a result being withheld.
 
 | split | RampNet | challengers | null-recall | GT-completeness corrected (#55) | notes |
 |---|---|---|---|---|---|
-| richmond | ✅ | ✅ all 8 | ✅ | ✅ 17% (5/29) | OOD deployment, Mapillary 360 |
-| bend | ✅ | ✅ all 8 | ✅ | ✅ 29% (7/24) | in-domain GSV reference |
-| clovis | ✅ | ✅ all 8 | ✅ | ✅ 30% (7/23) | hardest split — 2018 GoPro Fusion |
-| annapolis | ✅ | ✅ all 8 **+ Claude ×4** | ✅ | ✅ 22% (6/27) | survey-grade Trimble MX7; far-field finding; **only split with a Claude leg** (#122) |
-| morgantown | ✅ | ✅ all 8 | ✅ | ✅ 13% (4/30) | cleanest imagery; the control split |
-| paterson | ✅ | ✅ all 8 | ✅ | ✅ 20% (2/10) | second GSV city; live PS deployment; narrowest RampNet lead (0.12); 2nd Qwen inversion |
-| gainesville | ✅ | ✅ all 8 | ✅ | ✅ **35% (12/34) — highest measured** | third GSV city, first far-domain; same recall as paterson (0.647), opposite mechanism (ceiling 0.890); 3rd Qwen inversion |
-| budapest_district5 | ✅ | ✅ all 8 | ✅ | ✅ 26% (23/89) | **GT itself is low-confidence**; the one ranking inversion |
-| sao_paulo | ✅ | ✅ all 8 | ✅ | ✅ **12.5% (6/48) — lowest measured** | second non-US split (GSV, NBR 9050), GT **high** confidence — the budapest recall collapse did not replicate; 4th Qwen-32B caution occurrence, this time at parity not inversion |
-| manual_gold | ✅ | ✅ all 8 | ❌ too slow | n/a — un-anchored GT | 1k panos, the anchoring control |
-
-"All 8" is the roster in the class table below: RampNet, 2 Geminis, 2 Qwens, Molmo, OWLv2,
-Grounding DINO.
-
-**A ninth model, `gemini-3.7-flash`, has been run on all ten splits but is not in that roster
-and is not scored in the tables below.** Its detections are published and verified
-(`benchmark/model_detections/gemini-3.7-flash__*.json`, 10/10 pairs identical to the cache;
-see `docs/replication.md` for the exact commands, which need `--models gemini:gemini-3.7-flash`
-because it is off the default roster). Interim F1 numbers are on #20. It is held out of the
-roster tables until its write-up lands here, so that every row of every table below is one
-consistent 8-model set. **This is an omission of a write-up, not of a run** — the distinction
+| richmond | ✅ | ✅ full roster | ✅ | ✅ 17% (5/29) | OOD deployment, Mapillary 360 |
+| bend | ✅ | ✅ full roster | ✅ | ✅ 29% (7/24) | in-domain GSV reference |
+| clovis | ✅ | ✅ full roster | ✅ | ✅ 30% (7/23) | hardest split — 2018 GoPro Fusion |
+| annapolis | ✅ | ✅ full roster | ✅ | ✅ 22% (6/27) | survey-grade Trimble MX7; far-field finding; **only split with a Claude leg** (#122) |
+| morgantown | ✅ | ✅ full roster | ✅ | ✅ 13% (4/30) | cleanest imagery; the control split |
+| paterson | ✅ | ✅ full roster | ✅ | ✅ 20% (2/10) | second GSV city; live PS deployment; narrowest RampNet lead (0.12); 2nd Qwen inversion |
+| gainesville | ✅ | ✅ full roster | ✅ | ✅ **35% (12/34) — highest measured** | third GSV city, first far-domain; same recall as paterson (0.647), opposite mechanism (ceiling 0.890); 3rd Qwen inversion |
+| budapest_district5 | ✅ | ✅ full roster | ✅ | ✅ 26% (23/89) | **GT itself is low-confidence**; the one ranking inversion |
+| sao_paulo | ✅ | ✅ full roster | ✅ | ✅ **12.5% (6/48) — lowest measured** | second non-US split (GSV, NBR 9050), GT **high** confidence — the budapest recall collapse did not replicate; 4th Qwen-32B caution occurrence, this time at parity not inversion |
+| manual_gold | ✅ | ✅ full roster | ❌ too slow | n/a — un-anchored GT | 1k panos, the anchoring control |
+
+"Full roster" is the standing roster below. It is not a count written into this prose: the
+table is generated from `rampnet/roster.py`, which is the single place a model is registered,
+and `tests/test_roster.py` fails if the two stop agreeing. Regenerate it with
+`python -m rampnet.roster`.
+
+<!-- roster-table: generated by `python -m rampnet.roster` -->
+| model | provider | density | joined | scored below |
+| :--- | :--- | :--- | :--- | :--- |
+| `rampnet` | rampnet | sparse | 2026-07-22 | ✅ |
+| `gemini-3.6-flash` | gemini | sparse | 2026-07-22 | ✅ |
+| `gemini-3.1-pro-preview` | gemini | sparse | 2026-07-22 | ✅ |
+| `Qwen/Qwen3-VL-8B-Instruct` | qwen | sparse | 2026-07-22 | ✅ |
+| `Qwen/Qwen3-VL-32B-Instruct` | qwen | sparse | 2026-07-22 | ✅ |
+| `allenai/Molmo2-8B` | molmo | sparse | 2026-07-23 | ✅ |
+| `google/owlv2-large-patch14-ensemble` | owlv2 | dense | 2026-07-22 | ✅ |
+| `IDEA-Research/grounding-dino-base` | gdino | dense | 2026-07-22 | ✅ |
+| `gemini-3.7-flash` | gemini | sparse | 2026-08-14 | — published, not scored |
+
+**A model can be run, published and verified before its write-up lands**, and the last row is
+that case: `gemini-3.7-flash` has run on all ten splits, its detections are published and
+verified (`benchmark/model_detections/gemini-3.7-flash__*.json`, 10/10 pairs identical to the
+cache; `docs/replication.md` has the exact commands, which need
+`--models gemini:gemini-3.7-flash` because it is off the default roster), and interim F1
+numbers are on #20. It is held out of the scored tables so that every row of every table below
+is one consistent set. **This is an omission of a write-up, not of a run** — the distinction
 the matrix above exists to make, stated here because the artifact is already in the repo and
-would otherwise read as a withheld result.
+would otherwise read as a withheld result. Promoting it is one field in the registry plus a
+re-run; since #122 froze the #46 witness pool, doing so no longer disturbs that human pass.
 
 **Two more off-roster models, `claude-sonnet-5` and `claude-opus-5`, have been run on
 annapolis only** — four legs, both models × effort `low`/`high` (#122). They are likewise
@@ -77,7 +93,7 @@ harness does not record finish reasons — it infers from the shape of what was
 run with `finish_reason` captured would settle it directly, and would be worth doing if a
 future model shows a *higher* silent rate on ramp-dense panoramas specifically.
 
-**Every split again carries the full 8-model roster** — paterson's challenger +
+**Every split again carries the full standing roster** — paterson's challenger +
 null-recall runs landed 2026-07-29, hours after the split itself; gainesville's landed
 2026-07-30, the same day as its split; and sao_paulo's landed 2026-08-01, also the same day
 as its GT review (GPU legs on klone, Geminis via Vertex, all reproducible from the committed
@@ -1094,7 +1110,7 @@ nothing is detected the scale is wrong (try `--molmo-coord-scale`).
   cities — see the Molmo section; `MolmoPoint-8B`'s special-token path is wired but has not
   met real weights). Tested (`test_detection_eval.py`, `test_model_comparison.py`,
   `test_equirect_tiling.py`).
-- **Every split now carries the full 8-model roster** (morgantown and budapest_district5 run
+- **Every split now carries the full standing roster** (morgantown and budapest_district5 run
   2026-07-28). The remaining gaps, tracked in the coverage matrix at the top, are the
   GT-completeness correction (#55, done on two cities) and the null-recall pass on
   `manual_gold`.
@@ -1561,7 +1577,7 @@ Gemini needs no GPU at all — both models ran from a desktop against Vertex, pr
 ~4 h, flash in ~9 h. The GPU legs all ran happily on the **ckpt scavenger queue**
 (preemption costs ~one pano of cache).
 
-### Results (all 8 model groups)
+### Results (the full standing roster)
 
 Same protocol as the city tables: perspective tiling, match radius 0.022, box centers both
 sides. RampNet is shown at its published 0.55 operating point (the same detections score
diff --git a/docs/replication.md b/docs/replication.md
index f33df415..5f08bcf1 100644
--- a/docs/replication.md
+++ b/docs/replication.md
@@ -43,7 +43,10 @@ it into human-readable files, one per (model, split), keyed by panorama id with
 signature recorded inside. As of 2026-08-18 that is **112 files, 22.9 MB** — the seven-model
 roster across ten splits, plus the ten-split gemini-3.7-flash leg and the four annapolis
 Claude legs, both described below. `test_the_ledger_count_matches_the_directory` asserts
-this number against the directory, so it can no longer drift unnoticed.
+this number against the directory, so it can no longer drift unnoticed. Who is on the
+roster is `rampnet/roster.py`, not a count in this sentence; `rampnet` itself is a row in
+every results table but has no file here — it is read from each bundle's committed
+`records.jsonl` and carries no detector signature.
 
 ```bash
 python scripts/analysis/export_model_cache.py --out benchmark/model_detections
@@ -74,13 +77,19 @@ python scripts/analysis/export_model_cache.py --verify --models gemini:gemini-3.
 # -> compared 10 (model, split) pair(s); published detections score IDENTICALLY
 ```
 
-`gemini:gemini-3.7-flash` is **not** in `CHALLENGERS` (`scripts/analysis/fp_taxonomy.py`),
-which is what `--models` defaults to. So the two commands above are not optional detail: the
-default `--verify` skips these nine files entirely and reports a clean pass without opening
-them, `fp_taxonomy.py` needs the same `--models` flag, and `silent_witness.py` cannot reach
-them at all without adding the spec to `CHALLENGERS`. Adding it there would change the
-committed `fp_taxonomy.json` / `silent_witness.json`, so it is a re-run, not an edit — open
-until the leg's write-up lands in `docs/model_comparison.md`.
+`gemini:gemini-3.7-flash` is registered in `rampnet/roster.py` as published-but-off-roster,
+so it is not in `CHALLENGERS` and not what `--models` defaults to. The two commands above are
+therefore not optional detail: the default `--verify` skips these ten files entirely and
+reports a clean pass without opening them, and `fp_taxonomy.py` needs the same `--models`
+flag. Since #122, `silent_witness.py` takes `--models` as well, so it can be pointed at any
+pool without editing a tuple.
+
+Promoting the leg to the standing roster is one field in the registry (`standing=True`) plus a
+re-run of `fp_taxonomy.py` and `null_recall.py`, whose committed JSON would change — a re-run,
+not an edit, open until the write-up lands in `docs/model_comparison.md`. **What promotion no
+longer touches is the #46 human pass.** `silent_witness.py` defaults to
+`roster.WITNESS_POOL_46`, the pool frozen at the state the pass was rated under, and both
+committed artifacts record the pool they ran over.
 
 #### The four Claude legs are published, annapolis only, one file per effort level
 
@@ -629,7 +638,8 @@ python scripts/analysis/miss_gallery.py --bucket silent \
     --queue analysis_out/silent_witness.json --render analysis_out/gallery46_silent
 
 # 3. Confirm you are looking at the same images the first rater saw.
-#    The digest must equal the one in benchmark/miss_taxonomy_46/silent__manifest.json.
+#    It must equal the digest in benchmark/miss_taxonomy_46/silent_gallery/manifest.json,
+#    which is also recorded as `manifest_digest` inside every per-rater verdict file.
 python -c "import json;print(json.load(open('analysis_out/gallery46_silent/manifest.json'))['digest'])"
 #    -> 360b5ddf8751dcd0
 
diff --git a/rampnet/roster.py b/rampnet/roster.py
index 5a7e9ec2..5e25de57 100644
--- a/rampnet/roster.py
+++ b/rampnet/roster.py
@@ -230,6 +230,24 @@ def partition_by_density(specs):
     return sparse, dense
 
 
+#: Marks the generated roster table in a doc, so a test can find it and check it
+#: still matches the registry. Prose that restates a roster count drifts silently —
+#: docs/model_comparison.md said "all 8" and docs/replication.md "seven-model roster"
+#: at the same time, and both were written by hand.
+TABLE_MARKER = "<!-- roster-table: generated by `python -m rampnet.roster` -->"
+
+
+def markdown_table():
+    """The roster as a markdown table, for pasting under ``TABLE_MARKER`` in a doc."""
+    rows = ["| model | provider | density | joined | scored below |",
+            "| :--- | :--- | :--- | :--- | :--- |"]
+    for c in ROSTER:
+        scored = "✅" if c.standing else "— published, not scored"
+        density = c.density or "not yet measured"
+        rows.append(f"| `{c.label}` | {c.provider} | {density} | {c.added} | {scored} |")
+    return "\n".join(rows)
+
+
 def pool_record(specs, cargs=None):
     """A JSON-able description of a model pool, to embed in an analysis artifact.
 
@@ -244,3 +262,12 @@ def pool_record(specs, cargs=None):
     return {"pool": named, "specs": list(specs),
             "labels": [label_for(s, cargs) for s in specs],
             "sparse": list(sparse), "dense": list(dense)}
+
+
+if __name__ == "__main__":
+    import sys
+    # The table carries check marks, and a Windows console defaults to cp1252.
+    if hasattr(sys.stdout, "reconfigure"):
+        sys.stdout.reconfigure(encoding="utf-8")
+    print(TABLE_MARKER)
+    print(markdown_table())
diff --git a/scripts/analysis/README.md b/scripts/analysis/README.md
index d0fc5a9c..1378f11d 100644
--- a/scripts/analysis/README.md
+++ b/scripts/analysis/README.md
@@ -51,7 +51,7 @@ checkout.
 | `miss_decomposition.py` | no | Of the recall we're missing, how much can more data even reach? Splits misses into far-field (pixel-starved, 57.8%) and near-field (42.2%) with a multi-view ceiling (#59, #38, #48). Committed caches only. |
 | `miss_taxonomy.py` | no | **What actually caused each miss (#46).** Buckets every miss into merged / sub_threshold / localization / silent, so the near-field population above resolves into causes: only **0.023 of the 0.087 recall points is sourcing-addressable**. Includes a greedy-vs-optimal matcher check (a wash) and an azimuth-randomized null per bucket. Committed caches only. |
 | `fp_taxonomy.py` | no | **What the FP flood is made of (#46).** Buckets every model's false positives into duplicate / near_gt / hood / isolated, with an *exact* arc-geometry chance baseline for the near-GT share — which shows OWLv2's and Grounding DINO's near-ramp FPs are entirely density (excess −0.2% and −0.7%). Reads `.model_cache`; no GPU and no model load. |
-| `silent_witness.py` | no | Did any *other* model detect a ramp where RampNet was silent? Witnessed ⇒ the imagery contains a recognizable ramp, so the failure is RampNet-specific (confirmed vocabulary). Brackets the sourcing-addressable population at **0.009–0.022 recall pts**. Chance-corrected, because OWLv2 witnesses 121/128 by density alone. Reads `.model_cache`; no GPU. |
+| `silent_witness.py` | no | Did any *other* model detect a ramp where RampNet was silent? Witnessed ⇒ the imagery contains a recognizable ramp, so the failure is RampNet-specific (confirmed vocabulary). Brackets the sourcing-addressable population — see `docs/curb_ramp_data_sourcing.md` §0b for the current bracket, which is a function of the witness pool and so is not restated here. Chance-corrected, because the dense detectors witness most misses by density alone. `--models` defaults to the **frozen** `roster.WITNESS_POOL_46` (#122), the pool the #46 human pass was rated under; the pool it ran over is recorded in its JSON. Reads `.model_cache`; no GPU. |
 | `miss_gallery.py` | no | Crops for the misses geometry cannot explain (#46 gallery half). **Checks the instrument before rendering**: `geom()` sizes ramps at the model's 4096-px input, but stored panos run 4096–16384 px wide, so it classifies each crop `parity` vs `advantaged` and renders a third "as the model saw it" panel so a reviewer compares pixel budgets instead of inferring. Needs `benchmark/<city>/panos` (`--panos-root` if run from a worktree). |
 | `fp_gallery.py` | no | The FP half of the gallery: worst-N `isolated` false positives per model, through the same instrument and manifest as `miss_gallery.py`. Ranked by the model's own confidence where it has one; the sample size and what was left out are always printed, never silent. Reads `.model_cache` + `panos/`. |
 | `make_tagger.py <gallery>` | no | Turns a rendered gallery into a keyboard-driven `tagger.html` beside it — one keystroke per crop, auto-advance, `localStorage` autosave, and an export keyed exactly like `benchmark/<city>/incremental_fp_tags.json`. Picks the verdict scheme from the manifest's own contents (miss vs FP). Local page by design: the crops are git-ignored files on disk. |
@@ -59,7 +59,8 @@ checkout.
 | `plot_storage_floor.py` | no | Storage-floor cost + recall ceiling → `docs/figures/storage_floor_ceiling.png`. |
 
 `run_low_floor_extract.slurm` is the Hyak launcher for the one GPU step (one L40S, ~45 min for
-1,859 panos across all eight splits); it is resumable, skipping splits that already have a cache.
+1,859 panos across the splits it covers); it is resumable, skipping splits that already have a
+cache.
 Submitting from a non-interactive shell needs `PYTHON=<interpreter>` set explicitly — the
 `source activate sidewalkcv2` fallback only works from a conda-initialized login shell.
 
diff --git a/tests/test_roster.py b/tests/test_roster.py
index b7ad162b..07e68af5 100644
--- a/tests/test_roster.py
+++ b/tests/test_roster.py
@@ -59,6 +59,48 @@ def test_the_committed_verdicts_still_match_the_gallery_they_were_made_on():
     assert set(verdicts["verdicts"]) == set(manifest["items"])
 
 
+# --------------------------------------------------------------------------- #
+# The docs say what the registry says
+# --------------------------------------------------------------------------- #
+def test_the_roster_table_in_the_docs_matches_the_registry():
+    """The anti-drift mechanism for the docs is this test, not anyone's discipline.
+    Before #122 the roster count was hand-written in four files and two of them
+    disagreed — "all 8" in model_comparison.md against "seven-model roster" in
+    replication.md — while a ninth leg sat published in the repo."""
+    doc = (REPO / "docs" / "model_comparison.md").read_text("utf-8")
+    assert roster.TABLE_MARKER in doc, (
+        "the generated roster table is gone from docs/model_comparison.md; "
+        "regenerate it with `python -m rampnet.roster`")
+    after = doc.split(roster.TABLE_MARKER, 1)[1].lstrip("\n")
+    table = "\n".join(_table_lines(after))
+    assert table == roster.markdown_table(), (
+        "docs/model_comparison.md's roster table is stale; regenerate with "
+        "`python -m rampnet.roster`")
+
+
+def _table_lines(text):
+    for line in text.splitlines():
+        if not line.startswith("|"):
+            return
+        yield line
+
+
+def test_no_doc_still_hardcodes_the_old_roster_count():
+    """These exact phrases were the drift. Catch them coming back.
+
+    Whitespace is collapsed first, deliberately: every one of these was wrapped
+    across a line break in the prose, so a naive substring check finds none of them
+    and passes while the docs are still wrong.
+    """
+    import re
+    stale = ("all 8", "8-model roster", "seven-model roster", "all 8 model groups",
+             "8 model groups")
+    for name in ("model_comparison.md", "replication.md", "curb_ramp_data_sourcing.md"):
+        text = re.sub(r"\s+", " ", (REPO / "docs" / name).read_text("utf-8"))
+        for phrase in stale:
+            assert phrase not in text, f"docs/{name} still says {phrase!r}"
+
+
 # --------------------------------------------------------------------------- #
 # Registry consistency
 # --------------------------------------------------------------------------- #

From 0437d6776c6cf7b57438aa1696631c89e4f50d18 Mon Sep 17 00:00:00 2001
From: Jon Froehlich <jonf@cs.uw.edu>
Date: Tue, 18 Aug 2026 11:14:55 -0700
Subject: [PATCH 4/7] Register the legs the registry was missing: the YOLO trio
 and the four Claude legs (#122)

The registry claimed to be "every model the benchmark knows about, scored or
not". It covered 78 of the 112 files in benchmark/model_detections/. The three
supervised YOLO pano arms (30 files, #51) and the four annapolis Claude legs (4
files, #122) had been run, scored, verified and written up, and the one place
that is supposed to enumerate every model said nothing about them.

That gap is now a test rather than a promise. Two directions, both checked
against the directory instead of against prose:

  test_every_published_detections_file_belongs_to_a_registered_leg
  test_every_registered_leg_has_published_detections

plus test_each_published_file_names_the_leg_it_says_it_is, which is the one
check a clean clone can run with no cache at all: the filename, the
published_as recorded inside, the signature's model_id and the registry all
have to agree.

Registering the Claude legs needed a concept the registry did not have. Effort
is in the detection signature, so one model id is several legs with different
cache keys and different results, and both claude-sonnet-5 legs wanted the same
filename. Hence two fields:

  pins          the signature-entering knobs this leg holds, e.g.
                (("claude_effort", "high"),)
  published_as  the filename stem, defaulting to label -- because label cannot
                carry the pin. It is baked into cache keys that were already
                paid for, so renaming it orphans the detections.

BY_SPEC stays single-valued by holding only default legs (pins that match
PROVIDER_DEFAULTS), which is what a bare --models spec reproduces.
SCORED_SPECS is unchanged, so no analysis default moved: the YOLO arms in
particular must stay out of it, since it is the default --models of
fp_taxonomy, null_recall and silent_witness and a yolo: spec carries a local
checkpoint path.

Densities are measured off the published detections, per the registry's own
rule that density is evidence. The YOLO arms are 2.02-2.60 boxes/pano at the
headline conf 0.25 (4.42-9.39 at the 0.05 export floor); the Claude legs
1.56-3.73. All sparse.

Also: label_for now knows the yolo stem rule, mirroring YoloDetector's own
identity rule, so a yolo:<path> label is derived rather than overridden; slug()
moves to the roster so the directory test can spell a filename without
importing the exporter; and docs/replication.md's detection ledger now accounts
for all 112 files instead of 82, with the verification status of each group
stated rather than implied.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
---
 docs/model_comparison.md               |  32 ++++-
 docs/replication.md                    |  45 +++++--
 rampnet/roster.py                      | 162 +++++++++++++++++++++++--
 scripts/analysis/export_model_cache.py |   9 +-
 tests/test_roster.py                   |  99 +++++++++++++--
 5 files changed, 310 insertions(+), 37 deletions(-)

diff --git a/docs/model_comparison.md b/docs/model_comparison.md
index 81078bb9..25ca5108 100644
--- a/docs/model_comparison.md
+++ b/docs/model_comparison.md
@@ -30,7 +30,7 @@ and `tests/test_roster.py` fails if the two stop agreeing. Regenerate it with
 `python -m rampnet.roster`.
 
 <!-- roster-table: generated by `python -m rampnet.roster` -->
-| model | provider | density | joined | scored below |
+| leg | provider | density | joined | in the roster tables |
 | :--- | :--- | :--- | :--- | :--- |
 | `rampnet` | rampnet | sparse | 2026-07-22 | ✅ |
 | `gemini-3.6-flash` | gemini | sparse | 2026-07-22 | ✅ |
@@ -40,10 +40,23 @@ and `tests/test_roster.py` fails if the two stop agreeing. Regenerate it with
 | `allenai/Molmo2-8B` | molmo | sparse | 2026-07-23 | ✅ |
 | `google/owlv2-large-patch14-ensemble` | owlv2 | dense | 2026-07-22 | ✅ |
 | `IDEA-Research/grounding-dino-base` | gdino | dense | 2026-07-22 | ✅ |
-| `gemini-3.7-flash` | gemini | sparse | 2026-08-14 | — published, not scored |
-
-**A model can be run, published and verified before its write-up lands**, and the last row is
-that case: `gemini-3.7-flash` has run on all ten splits, its detections are published and
+| `gemini-3.7-flash` | gemini | sparse | 2026-08-14 | — published, not in these tables |
+| `y11l_pano` | yolo | sparse | 2026-08-14 | — published, not in these tables |
+| `y11x_pano_h200` | yolo | sparse | 2026-08-14 | — published, not in these tables |
+| `y26_pano` | yolo | sparse | 2026-08-14 | — published, not in these tables |
+| `claude-opus-5-effort-low` | claude | sparse | 2026-08-15 | — published, not in these tables |
+| `claude-opus-5-effort-high` | claude | sparse | 2026-08-15 | — published, not in these tables |
+| `claude-sonnet-5-effort-low` | claude | sparse | 2026-08-15 | — published, not in these tables |
+| `claude-sonnet-5-effort-high` | claude | sparse | 2026-08-15 | — published, not in these tables |
+
+**"Not in these tables" covers three different situations, and the difference matters.**
+The tables below are the zero-shot comparison; a leg can sit outside them because its
+write-up has not landed, because it is not zero-shot, or because it has run on one split
+rather than ten. Each is spelled out in that leg's `note` in `rampnet/roster.py`, and all
+three are omissions we are naming, not results being withheld.
+
+**A model can be run, published and verified before its write-up lands**, which is
+`gemini-3.7-flash`: it has run on all ten splits, its detections are published and
 verified (`benchmark/model_detections/gemini-3.7-flash__*.json`, 10/10 pairs identical to the
 cache; `docs/replication.md` has the exact commands, which need
 `--models gemini:gemini-3.7-flash` because it is off the default roster), and interim F1
@@ -62,6 +75,15 @@ where the whole result table is re-derived from those files by
 `tests/test_claude_annapolis_leg.py`. **The other nine splits have not been run** — that is
 a gap in coverage, not a withheld result, and closing it costs about $57 at `low` effort.
 
+**The three `y*_pano` rows are the supervised YOLO baseline** (#51), the one part of the
+registry that is not zero-shot. They have run on all ten splits and are scored, but under the
+pre-registered #71 protocol in their own section further down — mixing a trained detector into
+the zero-shot tables would make "best challenger" mean two different things in one column.
+They also stay out of `SCORED_SPECS` for a mechanical reason worth knowing before promoting
+anything: that tuple is the default `--models` of `fp_taxonomy`, `null_recall` and
+`silent_witness`, and a `yolo:` spec carries a local checkpoint path, so promoting them would
+break those three scripts on any clone without the weights.
+
 ### Are gemini-3.7-flash's silent panoramas real, or lost responses? (#120 review)
 
 The leg returns **nothing at all** on 345 of the 1,109 city-split panoramas (31.1%), against
diff --git a/docs/replication.md b/docs/replication.md
index 5f08bcf1..fa2e0144 100644
--- a/docs/replication.md
+++ b/docs/replication.md
@@ -32,21 +32,36 @@ lives on one machine.
 ### ✅ Resolved — the challenger detections are published
 
 `fp_taxonomy.py`, `silent_witness.py`, `complementarity.py` and `null_recall.py` all read the
-challenger detections (Gemini ×2, Qwen ×2, Molmo, OWLv2, Grounding DINO). Those cost real GPU-hours
-on Hyak and paid API spend, and until 2026-07-31 they lived only in a git-ignored `.model_cache/`,
-so every number they produced was reproducible on exactly one machine.
+challenger detections. Those cost real GPU-hours on Hyak and paid API spend, and until
+2026-07-31 they lived only in a git-ignored `.model_cache/`, so every number they produced was
+reproducible on exactly one machine. Which models those are is `rampnet/roster.py`, not a list
+in this sentence — the list here was one of the things that drifted.
 
 `.model_cache` is fine as a *working* cache and hostile as a published artifact: 12,951
 single-panorama shards keyed by an opaque SHA-1 of (label, signature, city, pano), unreadable
 without reconstructing detector signatures. `scripts/analysis/export_model_cache.py` consolidates
 it into human-readable files, one per (model, split), keyed by panorama id with the detector
-signature recorded inside. As of 2026-08-18 that is **112 files, 22.9 MB** — the seven-model
-roster across ten splits, plus the ten-split gemini-3.7-flash leg and the four annapolis
-Claude legs, both described below. `test_the_ledger_count_matches_the_directory` asserts
-this number against the directory, so it can no longer drift unnoticed. Who is on the
-roster is `rampnet/roster.py`, not a count in this sentence; `rampnet` itself is a row in
-every results table but has no file here — it is read from each bundle's committed
-`records.jsonl` and carries no detector signature.
+signature recorded inside. As of 2026-08-18 that is **112 files, 22.9 MB**, and every one of
+them belongs to a registered leg:
+
+| what | files | where it is written up |
+|---|---:|---|
+| the standing zero-shot roster, ten splits each (two Gemini legs are absent on `manual_gold`) | 68 | the roster tables in [`model_comparison.md`](model_comparison.md) |
+| `gemini-3.7-flash`, ten splits, published ahead of its write-up (#120) | 10 | §below |
+| the supervised YOLO pano trio, ten splits each (#51) | 30 | [`model_comparison.md` §supervised baseline](model_comparison.md), and the [training record](../scripts/model_comparison/yolo_baseline/README.md) |
+| the four annapolis Claude legs (#122) | 4 | [`model_comparison.md` §Claude](model_comparison.md) |
+
+`rampnet` is a row in every results table and has no file here: it is read from each bundle's
+committed `records.jsonl` and carries no detector signature.
+
+Two tests hold that table up rather than trust it.
+`test_the_ledger_count_matches_the_directory` asserts the count, and
+`test_every_published_detections_file_belongs_to_a_registered_leg` asserts the stronger
+property that nothing in the directory is unaccounted for. The second one is why this table
+exists: **the registry covered 78 of the 112 files.** The YOLO arms and the Claude legs had
+been run, scored, verified and written up, and the one place that is supposed to enumerate
+every model said nothing about them — which is also what the unremarked 78 → 108 jump in the
+drift list below actually was.
 
 ```bash
 python scripts/analysis/export_model_cache.py --out benchmark/model_detections
@@ -58,6 +73,16 @@ python scripts/analysis/export_model_cache.py --verify     # exported == cached
 that silently differs from what produced the paper's numbers is worse than none. It exits
 non-zero when it had nothing to compare, so a green run cannot mean "found no cache".
 
+The other 44 files were each verified the same way when they were published, but by their own
+invocation against their own cache rather than by the default-roster one above — the YOLO
+trio on makelab2 (30 files, identical to the producing cache; see the
+[training record](../scripts/model_comparison/yolo_baseline/README.md)) and the four Claude
+legs one at a time under `--publish-as` (see
+[`model_comparison.md`](model_comparison.md)). Re-running `--verify` on any of them needs the
+cache that produced it, which is machine-local by construction. What a clean clone can check
+without any cache is that each file's recorded signature still matches the leg the registry
+says it is: `test_each_published_file_names_the_leg_it_says_it_is`.
+
 **Keep this count current when a leg is added.** It drifted three times (61 → 68 at the São
 Paulo split, 68 → 78 at gemini-3.7-flash, 78 → 108 unremarked) before anyone noticed, and a
 ledger that exists to keep the repo honest is the wrong document to let rot. It is now a
diff --git a/rampnet/roster.py b/rampnet/roster.py
index 5e25de57..535f9b18 100644
--- a/rampnet/roster.py
+++ b/rampnet/roster.py
@@ -15,7 +15,7 @@
 literally rather than derived from ``ROSTER`` precisely so that adding a challenger
 cannot touch it. See the comment on it.
 
-Three properties of an entry are worth stating because they are easy to get wrong:
+Five properties of an entry are worth stating because they are easy to get wrong:
 
 * ``density`` is **evidence, not configuration** — it comes from the measured
   boxes-per-panorama in ``docs/model_comparison.md`` (sparse models emit 1-4, the
@@ -26,15 +26,43 @@
   A leg can be run, verified and committed long before its write-up lands
   (``gemini-3.7-flash``, #120); that is an omission of a write-up, not of a run, and
   the distinction is data here rather than prose in a doc.
-* ``label`` is the resolved model id used for result-table rows and for
-  ``benchmark/model_detections/<label>__<city>.json``. For nearly every provider it is
-  derivable from the spec; ``LABEL_OVERRIDES`` covers the ones where it is not.
+* ``label`` is the resolved model id: the result-table row, and the key the detection
+  cache is already written under. For nearly every provider it is derivable from the
+  spec; ``LABEL_OVERRIDES`` covers the ones where it is not.
+* ``pins`` is what makes a registered thing a **leg** rather than a model. A knob that
+  enters the detection signature splits one model id into several sets of detections:
+  ``claude-sonnet-5`` at effort ``low`` and at effort ``high`` are different runs with
+  different cache keys and different results. Each is its own entry, and ``pins``
+  names the knob it holds, as ``(("claude_effort", "high"),)``.
+* ``published_as`` is the filename stem under ``benchmark/model_detections/``, and it
+  defaults to ``label``. It exists because ``label`` cannot carry a pin: the label is
+  baked into cache keys that were already paid for, so renaming it orphans the
+  detections. The two came apart the first time a provider had a pin, and both legs
+  wanted ``claude-sonnet-5__annapolis.json``, the second silently overwriting the
+  first. **Once any leg of a model needs disambiguating, give every leg of that model
+  the same treatment** — a directory where one file is bare and its sibling is
+  qualified reads as though the bare one is the whole model.
 """
 from collections import namedtuple
+import os
+import re
 
-#: One registered model. ``spec`` is the ``compare.py --models`` token.
+
+def slug(label):
+    """Filesystem-safe model id.
+
+    ``IDEA-Research/grounding-dino-base`` -> ``IDEA-Research__grounding-dino-base``.
+    Defined here rather than in the exporter because the roster is what knows the set
+    of published names, and the test that checks the directory against the registry
+    must not import the exporter's dependencies to spell one filename.
+    """
+    return re.sub(r"[^A-Za-z0-9._-]+", "__", label)
+
+#: One registered leg. ``spec`` is the ``compare.py --models`` token; ``pins`` are the
+#: extra signature-entering settings it was run with, if any.
 Challenger = namedtuple(
-    "Challenger", "spec label provider density standing added note")
+    "Challenger", "spec label provider density standing added note pins published_as",
+    defaults=((), None))
 
 # --------------------------------------------------------------------------- #
 # The registry
@@ -95,6 +123,73 @@
              "Density measured 2026-08-18 off the published detections: 1.90 "
              "boxes/pano over 2,109 panos, against gemini-3.6-flash's 2.34 and "
              "OWLv2's 72.77."),
+
+    # The supervised YOLO baseline (#51). Ten splits each, scored under the
+    # pre-registered #71 protocol and written up in their own table in
+    # docs/model_comparison.md -- so they are published and scored, but not in the
+    # roster tables, which are the zero-shot comparison. Keeping them out of
+    # SCORED_SPECS is not bookkeeping: that tuple is the default --models of
+    # fp_taxonomy, null_recall and silent_witness, and a yolo spec carries a local
+    # .pt path, so promoting them would make three analysis scripts fail on any
+    # clone without the checkpoints.
+    Challenger(
+        spec="yolo:yolo_ckpts/y11l_pano.pt", label="y11l_pano", provider="yolo",
+        density="sparse", standing=False, added="2026-08-14",
+        note="YOLO11-L, pano geometry, 60 epochs. Best pano arm on seven of ten "
+             "splits. 2.11 boxes/pano at the headline conf 0.25, 4.79 at the 0.05 "
+             "floor the detections are published down to. The spec's path is the "
+             "convention its committed driver uses "
+             "(yolo_baseline/benchmark_eval/run_yolo_pano_eval.sh): fetch the "
+             "sha256-verified snapshot into yolo_ckpts/. Identity is the file stem "
+             "plus a weights content hash, not the path, so the cache key survives "
+             "being run from a different directory."),
+    Challenger(
+        spec="yolo:yolo_ckpts/y11x_pano_h200.pt", label="y11x_pano_h200",
+        provider="yolo", density="sparse", standing=False, added="2026-08-14",
+        note="YOLO11-X, the Tillicum-trained arm. 2.02 boxes/pano at 0.25, 4.42 at "
+             "0.05. Best arm in-distribution (manual_gold 0.851) and the highest AP "
+             "of the trio, at the lowest recall."),
+    Challenger(
+        spec="yolo:yolo_ckpts/y26_pano.pt", label="y26_pano", provider="yolo",
+        density="sparse", standing=False, added="2026-08-14",
+        note="YOLO26-L. The loosest of the trio -- 2.60 boxes/pano at 0.25 and 9.39 "
+             "at 0.05, roughly double the YOLO11 arms -- which is why it leads only "
+             "on budapest, where firing at all is the binding constraint."),
+
+    # The four annapolis Claude legs (#122). One split, so they cannot join tables
+    # the other rows report over ten; the write-up is annapolis-only for the same
+    # reason. Two model ids x two efforts: the first provider whose knob splits one
+    # id into several legs, hence `pins` and `published_as`.
+    Challenger(
+        spec="claude:claude-opus-5", label="claude-opus-5", provider="claude",
+        density="sparse", standing=False, added="2026-08-15",
+        pins=(("claude_effort", "low"),),
+        published_as="claude-opus-5-effort-low",
+        note="Top challenger on annapolis (F1 0.588), the first model to displace "
+             "gemini-3.1-pro. 2.56 boxes/pano. Effort low is the provider default, "
+             "so this is what a bare `claude:claude-opus-5` reproduces."),
+    Challenger(
+        spec="claude:claude-opus-5", label="claude-opus-5", provider="claude",
+        density="sparse", standing=False, added="2026-08-15",
+        pins=(("claude_effort", "high"),),
+        published_as="claude-opus-5-effort-high",
+        note="Same model, more thinking, worse F1 (127k thinking tokens to lose "
+             "0.068). 3.73 boxes/pano against low's 2.56: effort moves the "
+             "operating point, it does not raise the ceiling."),
+    Challenger(
+        spec="claude:claude-sonnet-5", label="claude-sonnet-5", provider="claude",
+        density="sparse", standing=False, added="2026-08-15",
+        pins=(("claude_effort", "low"),),
+        published_as="claude-sonnet-5-effort-low",
+        note="1.56 boxes/pano, the sparsest leg in the registry. Re-run after the "
+             "max_tokens truncation fix, so it covers all 125 panos."),
+    Challenger(
+        spec="claude:claude-sonnet-5", label="claude-sonnet-5", provider="claude",
+        density="sparse", standing=False, added="2026-08-15",
+        pins=(("claude_effort", "high"),),
+        published_as="claude-sonnet-5-effort-high",
+        note="1.98 boxes/pano. Loses F1 to effort in the same direction as Opus, "
+             "which is what makes that a pattern rather than one model's quirk."),
 )
 
 #: Specs whose label cannot be derived from the spec, because the ``model_id`` slot
@@ -161,7 +256,38 @@
 # --------------------------------------------------------------------------- #
 # Derived views — nothing below is hand-maintained
 # --------------------------------------------------------------------------- #
-BY_SPEC = {c.spec: c for c in ROSTER}
+def is_default_leg(c):
+    """True when this leg is what a bare ``--models <spec>`` reproduces.
+
+    A leg whose pins all match ``PROVIDER_DEFAULTS`` needs no extra flags; anything
+    else does. Only default legs go in ``BY_SPEC``, which is what keeps that mapping
+    single-valued now that one spec can name several legs.
+    """
+    return all(PROVIDER_DEFAULTS.get(k) == v for k, v in c.pins)
+
+
+def published_name(c):
+    """The filename stem a leg's detections are published under."""
+    return c.published_as or c.label
+
+
+def published_filename(c, city):
+    """``benchmark/model_detections/`` basename for one (leg, split)."""
+    return slug(published_name(c)) + "__" + city + ".json"
+
+
+#: The leg a bare spec resolves to. Legs with non-default pins are reachable through
+#: ``ROSTER`` and ``BY_PUBLISHED``, not here: a spec alone does not identify them.
+BY_SPEC = {c.spec: c for c in ROSTER if is_default_leg(c)}
+
+#: Every leg by the name its detections are published under -- the key that is unique
+#: by construction, because it is a filename.
+BY_PUBLISHED = {published_name(c): c for c in ROSTER}
+
+#: Legs with detections in ``benchmark/model_detections/``. ``rampnet`` is the one
+#: member of the roster with none: it is read from each bundle's committed
+#: ``records.jsonl`` and carries no detector signature.
+PUBLISHED = tuple(c for c in ROSTER if c.provider != "rampnet")
 
 #: Standing entries, RampNet included — the set every results table scores.
 SCORED = tuple(c for c in ROSTER if c.standing)
@@ -195,6 +321,11 @@ def label_for(spec, cargs=None):
     provider, _, model_id = spec.partition(":")
     provider, model_id = provider.strip(), model_id.strip()
     if model_id:
+        if provider == "yolo":
+            # A yolo spec carries a weights PATH, and the detector's identity is the
+            # file stem, not the path (detectors.YoloDetector), so that running the
+            # same checkpoint from a different directory hits the same cache.
+            return os.path.splitext(os.path.basename(model_id.replace(chr(92), "/")))[0]
         return model_id
     key = f"{provider}_model"
     if cargs is not None and getattr(cargs, key, None):
@@ -238,13 +369,22 @@ def partition_by_density(specs):
 
 
 def markdown_table():
-    """The roster as a markdown table, for pasting under ``TABLE_MARKER`` in a doc."""
-    rows = ["| model | provider | density | joined | scored below |",
+    """The roster as a markdown table, for pasting under ``TABLE_MARKER`` in a doc.
+
+    The first column is the leg's published name, not its ``label``: two legs of one
+    model share a label, and a table with the same row twice is worse than no table.
+    The last column is deliberately narrow -- "is this row in the tables below" --
+    because off-roster covers two different situations (a write-up that has not landed
+    yet, and a leg whose write-up is elsewhere in this doc), and which one applies is
+    in the entry's note, not in a check mark.
+    """
+    rows = ["| leg | provider | density | joined | in the roster tables |",
             "| :--- | :--- | :--- | :--- | :--- |"]
     for c in ROSTER:
-        scored = "✅" if c.standing else "— published, not scored"
+        scored = "✅" if c.standing else "— published, not in these tables"
         density = c.density or "not yet measured"
-        rows.append(f"| `{c.label}` | {c.provider} | {density} | {c.added} | {scored} |")
+        rows.append(f"| `{published_name(c)}` | {c.provider} | {density} | "
+                    f"{c.added} | {scored} |")
     return "\n".join(rows)
 
 
diff --git a/scripts/analysis/export_model_cache.py b/scripts/analysis/export_model_cache.py
index eb2a4c54..45e15f77 100644
--- a/scripts/analysis/export_model_cache.py
+++ b/scripts/analysis/export_model_cache.py
@@ -42,7 +42,6 @@
 import argparse
 import json
 import os
-import re
 import sys
 
 REPO = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
@@ -58,9 +57,11 @@
 PUBLISHED_DIR = os.path.join(REPO, "benchmark", "model_detections")
 
 
-def slug(label):
-    """Filesystem-safe model id. ``IDEA-Research/grounding-dino-base`` -> ``IDEA-Research__grounding-dino-base``."""
-    return re.sub(r"[^A-Za-z0-9._-]+", "__", label)
+#: Filesystem-safe model id, e.g. ``IDEA-Research/grounding-dino-base`` ->
+#: ``IDEA-Research__grounding-dino-base``. Defined in the roster so the test that
+#: checks this directory against the registry can spell a filename without importing
+#: the exporter; re-exported here because that is where callers look for it.
+slug = roster.slug
 
 
 def spec_label(spec, cargs):
diff --git a/tests/test_roster.py b/tests/test_roster.py
index 07e68af5..6cfc7523 100644
--- a/tests/test_roster.py
+++ b/tests/test_roster.py
@@ -104,13 +104,41 @@ def test_no_doc_still_hardcodes_the_old_roster_count():
 # --------------------------------------------------------------------------- #
 # Registry consistency
 # --------------------------------------------------------------------------- #
-def test_specs_and_labels_are_unique():
-    specs = [c.spec for c in roster.ROSTER]
-    labels = [c.label for c in roster.ROSTER]
-    assert len(specs) == len(set(specs))
-    # Labels are filenames in benchmark/model_detections; a collision would have two
-    # models overwriting each other's published detections.
-    assert len(labels) == len(set(labels))
+def test_a_bare_spec_names_exactly_one_leg():
+    """One spec can name several legs once a pin is involved, but only one of them is
+    what running that spec with no extra flags reproduces."""
+    default = [c.spec for c in roster.ROSTER if roster.is_default_leg(c)]
+    assert len(default) == len(set(default))
+    assert set(roster.BY_SPEC) == set(default)
+
+
+def test_published_names_are_unique():
+    """These are filenames. A collision does not raise -- the second leg overwrites
+    the first, leaving a file that still looks complete and still passes --verify.
+    That is exactly how the two claude-sonnet-5 legs collided (#122)."""
+    names = [roster.published_name(c) for c in roster.ROSTER]
+    assert len(names) == len(set(names))
+
+
+def test_a_pinned_leg_is_published_under_a_name_that_says_so():
+    """If a pin changes the detections, the filename has to change with it, or the
+    directory claims one set of detections is the whole model."""
+    for c in roster.ROSTER:
+        if not c.pins:
+            continue
+        assert c.published_as, c.spec
+        for _, value in c.pins:
+            assert str(value) in c.published_as, (c.published_as, c.pins)
+
+
+def test_every_leg_of_a_pinned_model_is_qualified():
+    """Half-qualified is worse than unqualified: a bare `claude-sonnet-5__annapolis`
+    sitting next to `claude-sonnet-5-effort-high__annapolis` reads as the model
+    rather than as one of its legs."""
+    pinned = {c.label for c in roster.ROSTER if c.pins}
+    for c in roster.ROSTER:
+        if c.label in pinned:
+            assert c.published_as, (c.label, "sibling leg is pinned")
 
 
 def test_every_entry_label_is_what_label_for_resolves():
@@ -150,6 +178,63 @@ def test_every_entry_records_when_it_joined():
         assert c.note, c.spec
 
 
+# --------------------------------------------------------------------------- #
+# The registry and the published detections are the same statement
+# --------------------------------------------------------------------------- #
+DETECTIONS = REPO / "benchmark" / "model_detections"
+
+
+def _published_files():
+    return sorted(p.name for p in DETECTIONS.glob("*__*.json"))
+
+
+def test_every_published_detections_file_belongs_to_a_registered_leg():
+    """The registry claims to be every model the benchmark knows about. This is that
+    claim, checked against the directory rather than against prose.
+
+    It caught the gap it was written for: the registry covered 78 of 112 files. The
+    three supervised YOLO arms (30 files, #51) and the four annapolis Claude legs (4
+    files, #122) were published, scored and written up while the one place that is
+    supposed to list them said nothing about them.
+    """
+    known = {roster.slug(roster.published_name(c)) for c in roster.ROSTER}
+    orphans = sorted({f.rsplit("__", 1)[0] for f in _published_files()} - known)
+    assert not orphans, (
+        "published detections with no roster entry: " + ", ".join(orphans) +
+        " -- add them to rampnet/roster.py")
+
+
+def test_every_registered_leg_has_published_detections():
+    """The other direction. An entry with no files is a model someone meant to run,
+    or a name that drifted from the filename it is supposed to predict."""
+    missing = [roster.published_name(c) for c in roster.PUBLISHED
+               if not list(DETECTIONS.glob(roster.slug(roster.published_name(c)) + "__*.json"))]
+    assert not missing, "registered but nothing published: " + ", ".join(missing)
+
+
+def test_rampnet_is_the_only_roster_member_without_detections():
+    """It is read from each bundle's committed records.jsonl and carries no detector
+    signature, which is why it is the one row with no file here."""
+    assert {c.spec for c in roster.ROSTER} - {c.spec for c in roster.PUBLISHED} == {"rampnet"}
+
+
+def test_each_published_file_names_the_leg_it_says_it_is():
+    """The filename, the `published_as` recorded inside, and the registry all have to
+    agree, or a file can be renamed into a different leg's identity."""
+    for name in _published_files():
+        stem, _, _ = name.rpartition("__")
+        entry = next((c for c in roster.ROSTER
+                      if roster.slug(roster.published_name(c)) == stem), None)
+        assert entry is not None, name
+        payload = json.loads((DETECTIONS / name).read_text("utf-8"))
+        assert payload["model"] == entry.label, name
+        assert payload.get("published_as", entry.label) == roster.published_name(entry), name
+        assert payload["signature"]["model_id"] == entry.label, name
+        for key, value in entry.pins:
+            sig_key = key.split("_", 1)[1]          # claude_effort -> effort
+            assert payload["signature"][sig_key] == value, (name, key)
+
+
 # --------------------------------------------------------------------------- #
 # density_of / partition_by_density refuse to guess
 # --------------------------------------------------------------------------- #

From e4d3d1de425aa203fb0961bc8cd351a06f0808d0 Mon Sep 17 00:00:00 2001
From: Jon Froehlich <jonf@cs.uw.edu>
Date: Tue, 18 Aug 2026 11:18:19 -0700
Subject: [PATCH 5/7] Refuse to start a paid leg that will not record what it
 spent (#122)

report_usage warns when a leg finishes with no log destination. That warning
cannot save the run it fires on: by the time it prints, the tokens are bought,
and token counts are the one artifact that cannot be back-filled -- a re-run
reads the detection cache, makes zero API calls, and can never reproduce them.
The four Claude legs' $28.82 is unrecoverable for exactly that reason.

So the check moves to before the money is spent. compare.py now errors out on
--usage-log none when any selected provider is paid, with
--allow-unrecorded-spend as a named, visible override -- a guard with no
override gets edited out instead, which is worse.

Which providers cost money is roster.PAID_PROVIDERS, and a test asserts that
every model priced in pricing.py has its provider in that set, so the guard
cannot develop a hole exactly where money is being spent.

The end-of-run warning stays: it still covers the case where a log path existed
but could not be written.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
---
 docs/model_comparison.md            | 11 ++++--
 rampnet/roster.py                   |  9 +++++
 scripts/model_comparison/compare.py | 21 ++++++++++-
 tests/test_model_comparison.py      | 58 +++++++++++++++++++++++++++++
 4 files changed, 95 insertions(+), 4 deletions(-)

diff --git a/docs/model_comparison.md b/docs/model_comparison.md
index 25ca5108..dbe59683 100644
--- a/docs/model_comparison.md
+++ b/docs/model_comparison.md
@@ -1332,9 +1332,14 @@ done; done
 per-leg costs in the table above come from the runs' console output, not from a committed
 record. A re-run cannot back-fill them either — the detections are cached, so a repeat run
 makes zero API calls and has no usage to report. Only the 2026-08-18 single-panorama
-re-run ($0.03) is in the log. `report_usage` now warns loudly when a leg that spent money
-finishes with no log destination, which is the check that would have caught this while the
-money was being spent.
+re-run ($0.03) is in the log.
+
+Two guards now stand where that went wrong, and the order matters. `compare.py` **refuses to
+start** a paid leg under `--usage-log none` (override: `--allow-unrecorded-spend`), which is
+the check that fires while the money is still unspent; `report_usage` still warns loudly at
+the end of a leg that logged nothing, for the case where the log path existed but could not
+be written. A warning after the fact could not have saved these four legs — by the time it
+prints, the tokens are bought and the counts are already unrecoverable.
 
 ## Cost accounting for paid models
 
diff --git a/rampnet/roster.py b/rampnet/roster.py
index 535f9b18..0fcf3069 100644
--- a/rampnet/roster.py
+++ b/rampnet/roster.py
@@ -253,6 +253,15 @@ def slug(label):
     "yolo_imgsz": 1024,
 }
 
+#: Providers whose calls cost money. The list is here rather than in a script
+#: because it is registry knowledge, and because two separate checks need it: the
+#: cost estimate in pricing.py, and compare.py's refusal to start a paid leg with
+#: usage logging switched off. Token counts are the one artifact that cannot be
+#: back-filled -- a re-run reads the detection cache, makes zero calls, and so can
+#: never reproduce them -- which is how the four Claude legs' $28.82 ended up with
+#: no committed record.
+PAID_PROVIDERS = frozenset({"gemini", "claude"})
+
 # --------------------------------------------------------------------------- #
 # Derived views — nothing below is hand-maintained
 # --------------------------------------------------------------------------- #
diff --git a/scripts/model_comparison/compare.py b/scripts/model_comparison/compare.py
index 39b6d244..095a442c 100644
--- a/scripts/model_comparison/compare.py
+++ b/scripts/model_comparison/compare.py
@@ -633,7 +633,13 @@ def main():
                     help="Append one JSONL record per paid-model run (token counts + "
                          f"estimated cost; see pricing.py). Default: {DEFAULT_USAGE_LOG_REL} "
                          "(tracked in git — the spend record is a durable research fact, "
-                         "not scratch). Pass 'none' to disable.")
+                         "not scratch). Pass 'none' to disable, which a paid model "
+                         "refuses to run under unless --allow-unrecorded-spend is given "
+                         "too.")
+    ap.add_argument("--allow-unrecorded-spend", action="store_true",
+                    help="Permit a paid model to run with --usage-log none. Needed only "
+                         "to spend money without recording what it cost, which is not "
+                         "recoverable afterwards; say why in the PR if you use it.")
     args = ap.parse_args()
 
     load_dotenv(str(REPO_ROOT))
@@ -663,6 +669,19 @@ def main():
     city = os.path.basename(os.path.normpath(args.bundle))
     cache = DetectionCache(args.cache_dir, enabled=not args.no_cache)
     usage_log = None if args.usage_log == "none" else args.usage_log
+    # Fail BEFORE the money is spent, not after. report_usage warns at the end of a
+    # leg that logged nothing, but by then the tokens are bought and the counts are
+    # already unrecoverable: a re-run reads the detection cache, makes zero API
+    # calls, and can never reproduce them. That is exactly how the four Claude legs
+    # (#122) ended up costing $28.82 with no committed record.
+    if usage_log is None and not args.allow_unrecorded_spend:
+        paid = sorted({p for p, _ in specs if p in roster.PAID_PROVIDERS})
+        if paid:
+            ap.error(
+                f"--usage-log none with paid provider(s) {', '.join(paid)}. Token "
+                f"counts cannot be back-filled — a cached re-run makes no API calls — "
+                f"so this would spend money that no committed artifact records. Drop "
+                f"--usage-log none, or pass --allow-unrecorded-spend deliberately.")
 
     print(f"Bundle: {args.bundle}  ({len(gts)} scored panos)  "
           f"match radius {args.radius}  ground truth: {gt_desc}")
diff --git a/tests/test_model_comparison.py b/tests/test_model_comparison.py
index f5629914..29d735b1 100644
--- a/tests/test_model_comparison.py
+++ b/tests/test_model_comparison.py
@@ -1256,6 +1256,64 @@ def test_a_paid_leg_with_the_usage_log_disabled_says_so_loudly(capsys):
     assert "WARNING" in out and "not recorded" in out.lower()
 
 
+# --- ... and the run refuses to start in the first place --------------------
+
+def _run_compare(argv, monkeypatch):
+    """Invoke compare.main() as the CLI would, returning (SystemExit code, stderr)."""
+    import compare
+    monkeypatch.setattr(sys, "argv", ["compare.py"] + argv)
+    with pytest.raises(SystemExit) as exc:
+        compare.main()
+    return exc.value.code
+
+
+@pytest.mark.parametrize("spec", ["claude:claude-opus-5", "gemini:gemini-3.6-flash",
+                                  "rampnet,claude:claude-sonnet-5"])
+def test_a_paid_run_refuses_to_start_with_the_usage_log_disabled(spec, monkeypatch,
+                                                                 capsys):
+    """The warning in report_usage fires AFTER the tokens are bought, which is too
+    late for the one artifact that cannot be back-filled. This fires before."""
+    code = _run_compare([os.path.join(REPO_ROOT, "benchmark", "annapolis"), "--models", spec,
+                         "--usage-log", "none"], monkeypatch)
+    assert code != 0
+    err = capsys.readouterr().err
+    assert "--usage-log none" in err and "back-filled" in err
+
+
+def test_a_free_model_may_run_without_a_usage_log(monkeypatch):
+    """The check is about spend, not about logging for its own sake. A local model
+    costs nothing, so requiring a spend record from it would be noise."""
+    import compare
+    monkeypatch.setattr(sys, "argv", ["compare.py", os.path.join(REPO_ROOT, "benchmark", "annapolis"),
+                                      "--models", "rampnet", "--usage-log", "none",
+                                      "--limit", "1"])
+    compare.main()          # must not raise SystemExit
+
+
+def test_unrecorded_spend_stays_possible_but_deliberate(monkeypatch):
+    """A guard with no override gets worked around by editing it out, which is
+    worse. The override is a named flag, so using it is visible in the command."""
+    import compare
+    monkeypatch.setattr(sys, "argv", ["compare.py", os.path.join(REPO_ROOT, "benchmark", "annapolis"),
+                                      "--models", "claude:claude-opus-5",
+                                      "--usage-log", "none", "--allow-unrecorded-spend",
+                                      "--limit", "1"])
+    compare.main()          # reaches the run; the leg itself is "not runnable" here
+
+
+def test_the_paid_provider_list_covers_every_priced_model():
+    """pricing.py knows what a model costs; the roster knows which providers cost
+    anything. If a priced model's provider is not in PAID_PROVIDERS, the guard has
+    a hole exactly where money is being spent."""
+    from rampnet import roster
+    import pricing
+    for model_id in pricing.PRICING:
+        provider = next((c.provider for c in roster.ROSTER if c.label == model_id), None)
+        if provider is None:
+            continue                     # priced but not registered (e.g. retired alias)
+        assert provider in roster.PAID_PROVIDERS, model_id
+
+
 # --- the provider roster has ONE source of truth ----------------------------
 
 def test_every_provider_is_listed_everywhere_a_user_looks():

From 16315eaaae2271025b881d147620c45103098431 Mon Sep 17 00:00:00 2001
From: Jon Froehlich <jonf@cs.uw.edu>
Date: Tue, 18 Aug 2026 12:28:24 -0700
Subject: [PATCH 6/7] Fix all 15 review findings on #128 (#122)

Two were real defects with teeth; the rest were the registry knowing something
the code around it never asked.

**A test could spend money.** test_unrecorded_spend_stays_possible_but_deliberate
drove compare.main() into score_model with a paid model and --usage-log none, so
`pytest -q` was one cache miss away from a billed call -- written by the commit
that exists to stop unrecorded spend. All four spend tests now drive score_model
directly with a stub detector whose prepare() raises, so a guard that let a run
through fails loudly instead of quietly reaching for the network. No bundle, no
credentials, 0.42 s.

**The guard also refused runs that cannot spend.** Keying on provider at parse
time rejected a fully cached re-score, which skips the model load and makes zero
calls -- the exact path the published detections exist to keep open. The check
moved into score_model, at the first uncached pano: still before any money moves,
and now it raises UnrecordedSpend, which main() deliberately does not swallow
into its "not runnable" handler.

**Promotion was broken for a pinned leg.** standing=True on a pinned entry put
its spec in CHALLENGERS while BY_SPEC resolved it to the sibling default leg, so
the tables would claim one leg and fp_taxonomy/null_recall would score the
other's detections and read its density. Now rejected at import with an
explanation, SPARSE/DENSE derive from entries rather than a spec lookup that
could KeyError at module scope, and a test covers it.

The rest:

- label_for applies the yolo stem rule to --yolo-model too, not just to a path
  inside the spec; both spellings now agree with YoloDetector (was: a whole path
  slugged into a filename that was never written, then a cache miss on every
  pano reported as "no cache entry").
- The exporter asks the registry for a leg's published name (new roster.leg_for
  + publication_name) instead of depending on --publish-as being remembered.
  Forgetting it wrote the bare model id, which collides with nothing, so the
  overwrite guard stayed quiet. published_filename/BY_PUBLISHED are now used
  rather than hand-rolled in the tests.
- compare.py grows build_parser(), so test_provider_defaults_match_compare_pys_parser
  actually runs. It had skipped unconditionally its whole life while reading as
  coverage of the most load-bearing invariant here.
- build_detector's fallbacks and the private Args in size_analysis.py and
  depth_extract_da3.py read PROVIDER_DEFAULTS; five more copies of values that
  feed the cache signature are gone.
- fp_taxonomy builds its pool record BEFORE scoring, so an unregistered spec
  fails in a second instead of after every model is scored -- and only for runs
  that were going to write an artifact.
- Two comments stated things that are false: SCORED_SPECS is not silent_witness's
  default (this PR made that WITNESS_POOL_46, which is the point of the freeze),
  and pricing.py does not consume PAID_PROVIDERS.
- silent_witness's vestigial SPARSE/DENSE and unused CHALLENGERS import are gone;
  their tests now assert over the frozen pool the script actually runs.
- The stale-phrase doc guard no longer has an entry that is a prefix of another,
  no longer rejects a legitimate "all 8 splits", and covers scripts/analysis/README.md.
- Ledger drift list runs to 112; _run_compare's wrong docstring went with the
  test rewrite.

Suite 1,100 -> 1,102 passed, 1 skipped.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
---
 docs/model_comparison.md               |   8 +-
 docs/replication.md                    |   2 +-
 rampnet/roster.py                      |  89 ++++++++++++++++-----
 scripts/analysis/depth_extract_da3.py  |  15 +++-
 scripts/analysis/export_model_cache.py |  30 ++++++-
 scripts/analysis/fp_taxonomy.py        |   8 +-
 scripts/analysis/silent_witness.py     |  18 +++--
 scripts/analysis/size_analysis.py      |  15 +++-
 scripts/model_comparison/compare.py    |  68 +++++++++++-----
 scripts/model_comparison/detectors.py  |  30 +++++--
 tests/test_export_model_cache.py       |  23 +++++-
 tests/test_model_comparison.py         | 105 ++++++++++++++++---------
 tests/test_roster.py                   |  41 +++++++---
 tests/test_silent_witness.py           |  16 ++--
 14 files changed, 347 insertions(+), 121 deletions(-)

diff --git a/docs/model_comparison.md b/docs/model_comparison.md
index dbe59683..b98026c2 100644
--- a/docs/model_comparison.md
+++ b/docs/model_comparison.md
@@ -80,9 +80,11 @@ registry that is not zero-shot. They have run on all ten splits and are scored,
 pre-registered #71 protocol in their own section further down — mixing a trained detector into
 the zero-shot tables would make "best challenger" mean two different things in one column.
 They also stay out of `SCORED_SPECS` for a mechanical reason worth knowing before promoting
-anything: that tuple is the default `--models` of `fp_taxonomy`, `null_recall` and
-`silent_witness`, and a `yolo:` spec carries a local checkpoint path, so promoting them would
-break those three scripts on any clone without the weights.
+anything: that tuple is the default `--models` of `fp_taxonomy` and `null_recall`, and a
+`yolo:` spec carries a local checkpoint path, so promoting them would break both on any clone
+without the weights. `silent_witness` is not in that list — it defaults to the frozen
+`WITNESS_POOL_46`, so the #46 human pass is unaffected by any promotion, which is what the
+freeze is for.
 
 ### Are gemini-3.7-flash's silent panoramas real, or lost responses? (#120 review)
 
diff --git a/docs/replication.md b/docs/replication.md
index fa2e0144..5f711257 100644
--- a/docs/replication.md
+++ b/docs/replication.md
@@ -84,7 +84,7 @@ without any cache is that each file's recorded signature still matches the leg t
 says it is: `test_each_published_file_names_the_leg_it_says_it_is`.
 
 **Keep this count current when a leg is added.** It drifted three times (61 → 68 at the São
-Paulo split, 68 → 78 at gemini-3.7-flash, 78 → 108 unremarked) before anyone noticed, and a
+Paulo split, 68 → 78 at gemini-3.7-flash, 78 → 108 unremarked — that one was the YOLO trio, see the table above — and 108 → 112 at the Claude legs) before anyone noticed, and a
 ledger that exists to keep the repo honest is the wrong document to let rot. It is now a
 test rather than a promise.
 
diff --git a/rampnet/roster.py b/rampnet/roster.py
index 0fcf3069..d4f94444 100644
--- a/rampnet/roster.py
+++ b/rampnet/roster.py
@@ -129,9 +129,11 @@ def slug(label):
     # docs/model_comparison.md -- so they are published and scored, but not in the
     # roster tables, which are the zero-shot comparison. Keeping them out of
     # SCORED_SPECS is not bookkeeping: that tuple is the default --models of
-    # fp_taxonomy, null_recall and silent_witness, and a yolo spec carries a local
-    # .pt path, so promoting them would make three analysis scripts fail on any
-    # clone without the checkpoints.
+    # fp_taxonomy and null_recall, and a yolo spec carries a local .pt path, so
+    # promoting them would make both fail on any clone without the checkpoints.
+    # (silent_witness defaults to WITNESS_POOL_46, not to SCORED_SPECS, so the
+    # frozen human pass is unaffected either way -- that is the point of the
+    # freeze.)
     Challenger(
         spec="yolo:yolo_ckpts/y11l_pano.pt", label="y11l_pano", provider="yolo",
         density="sparse", standing=False, added="2026-08-14",
@@ -253,11 +255,12 @@ def slug(label):
     "yolo_imgsz": 1024,
 }
 
-#: Providers whose calls cost money. The list is here rather than in a script
-#: because it is registry knowledge, and because two separate checks need it: the
-#: cost estimate in pricing.py, and compare.py's refusal to start a paid leg with
-#: usage logging switched off. Token counts are the one artifact that cannot be
-#: back-filled -- a re-run reads the detection cache, makes zero calls, and so can
+#: Providers whose calls cost money -- registry knowledge, so it lives here rather
+#: than in the one script that currently reads it (compare.py's refusal to spend
+#: without recording it). Note this is per PROVIDER, while pricing.py prices per
+#: MODEL ID and does not consult it; `test_the_paid_provider_list_covers_every_priced_model`
+#: is what keeps the two from disagreeing. Token counts are the one artifact that
+#: cannot be back-filled -- a re-run reads the detection cache, makes zero calls, and so can
 #: never reproduce them -- which is how the four Claude legs' $28.82 ended up with
 #: no committed record.
 PAID_PROVIDERS = frozenset({"gemini", "claude"})
@@ -298,6 +301,21 @@ def published_filename(c, city):
 #: ``records.jsonl`` and carries no detector signature.
 PUBLISHED = tuple(c for c in ROSTER if c.provider != "rampnet")
 
+# A standing leg must be reproducible from its spec alone, because that is all the
+# scored tuples below carry. A pinned leg is not: `--models claude:claude-opus-5`
+# gives you the LOW-effort leg whatever the roster row says, so promoting the high
+# one would have the tables claim one leg while fp_taxonomy and null_recall scored
+# the other's detections, and read its density off the other's measurement. Caught
+# here, at import, rather than as a wrong number in a table.
+for _c in ROSTER:
+    if _c.standing and _c.pins:
+        raise ValueError(
+            f"{_c.spec!r} is standing but pinned {dict(_c.pins)!r}. A scored entry has "
+            f"to be what a bare --models spec reproduces, and the pinned legs of one "
+            f"spec are indistinguishable there. Give the leg its own spec first, or "
+            f"score it in its own table with standing=False.")
+del _c
+
 #: Standing entries, RampNet included — the set every results table scores.
 SCORED = tuple(c for c in ROSTER if c.standing)
 
@@ -310,11 +328,29 @@ def published_filename(c, city):
 #: Published and verified, but not scored in the roster tables.
 OFF_ROSTER = tuple(c for c in ROSTER if not c.standing)
 
+# Read off the entries, not by looking each spec back up in BY_SPEC: that mapping
+# holds default legs only, so a spec-keyed lookup here would resolve to the wrong
+# leg (or raise at import) the moment anything pinned reached this far. The check
+# above makes that unreachable; deriving straight from the entry makes it moot.
 #: Sparse enough that a hit is evidence rather than coverage.
-SPARSE = tuple(s for s in CHALLENGERS if BY_SPEC[s].density == "sparse")
+SPARSE = tuple(c.spec for c in SCORED
+               if c.provider != "rampnet" and c.density == "sparse")
 
 #: So dense that a hit is mostly coverage; reported, never used for a headline.
-DENSE = tuple(s for s in CHALLENGERS if BY_SPEC[s].density == "dense")
+DENSE = tuple(c.spec for c in SCORED
+              if c.provider != "rampnet" and c.density == "dense")
+
+
+def weights_stem(path):
+    """A yolo checkpoint's identity: the file stem, not the path.
+
+    ``detectors.YoloDetector`` keys its cache on this so the same checkpoint hits
+    the same entries from a different working directory. Both spellings of a yolo
+    run reach it -- ``--models yolo:<path>`` and ``--models yolo --yolo-model
+    <path>`` -- because a label that agreed with the detector on one and not the
+    other is the cache-key drift this registry exists to remove.
+    """
+    return os.path.splitext(os.path.basename(str(path).replace(chr(92), "/")))[0]
 
 
 def label_for(spec, cargs=None):
@@ -330,18 +366,35 @@ def label_for(spec, cargs=None):
     provider, _, model_id = spec.partition(":")
     provider, model_id = provider.strip(), model_id.strip()
     if model_id:
-        if provider == "yolo":
-            # A yolo spec carries a weights PATH, and the detector's identity is the
-            # file stem, not the path (detectors.YoloDetector), so that running the
-            # same checkpoint from a different directory hits the same cache.
-            return os.path.splitext(os.path.basename(model_id.replace(chr(92), "/")))[0]
-        return model_id
+        return weights_stem(model_id) if provider == "yolo" else model_id
     key = f"{provider}_model"
-    if cargs is not None and getattr(cargs, key, None):
-        return getattr(cargs, key)
+    value = getattr(cargs, key, None) if cargs is not None else None
+    if value:
+        # ...including when the path arrives as --yolo-model rather than in the spec.
+        return weights_stem(value) if provider == "yolo" else value
     return PROVIDER_DEFAULTS.get(key, provider)
 
 
+def leg_for(spec, cargs=None):
+    """The registered leg a run resolves to, or ``None`` if it is not registered.
+
+    A spec alone is not enough once pins exist, so the pinned settings are read off
+    ``cargs`` and matched: ``claude:claude-opus-5`` with ``claude_effort='high'``
+    is a different leg from the same spec at ``low``. This is what lets the exporter
+    name a file without being told (see ``published_name``) instead of relying on
+    whoever ran it to remember ``--publish-as``.
+    """
+    label = label_for(spec, cargs)
+    candidates = [c for c in ROSTER if c.spec == spec or c.label == label]
+    for c in candidates:                      # a pinned leg wins when its pins match
+        if c.pins and all(getattr(cargs, k, None) == v for k, v in c.pins):
+            return c
+    for c in candidates:                      # otherwise the leg the bare spec names
+        if not c.pins:
+            return c
+    return None
+
+
 def density_of(spec):
     """``"sparse"`` or ``"dense"`` for a registered spec.
 
diff --git a/scripts/analysis/depth_extract_da3.py b/scripts/analysis/depth_extract_da3.py
index 6e0b72a5..c15ea290 100644
--- a/scripts/analysis/depth_extract_da3.py
+++ b/scripts/analysis/depth_extract_da3.py
@@ -25,6 +25,7 @@
 
 import numpy as np
 import torch
+from rampnet import roster  # noqa: E402
 from rampnet.detection_eval import (
     build_ground_truth, radius_sq_for, PANO_SCALE_X, PANO_SCALE_Y, _xy, prediction_confidence)
 from compare import load_bundle, DetectionCache, cache_key
@@ -41,8 +42,18 @@
 
 
 class Args:
-    gemini_model = PRO; qwen_model = "Qwen/Qwen3-VL-8B-Instruct"
-    qwen_coord_space = "auto"; tiling = "perspective"
+    """The build_detector namespace this script hands in.
+
+    Provider model ids come from the registry rather than being retyped: they feed
+    the detection cache signature, so a literal here that drifts from
+    PROVIDER_DEFAULTS does not crash, it silently misses every cached detection.
+    `gemini_model` is deliberately NOT the registry default -- this analysis is
+    pinned to the pro leg -- which is exactly why it is the one line worth stating.
+    """
+    gemini_model = PRO
+    qwen_model = roster.PROVIDER_DEFAULTS["qwen_model"]
+    qwen_coord_space = roster.PROVIDER_DEFAULTS["qwen_coord_space"]
+    tiling = "perspective"
 
 
 def geom_dist(y):
diff --git a/scripts/analysis/export_model_cache.py b/scripts/analysis/export_model_cache.py
index 45e15f77..54425014 100644
--- a/scripts/analysis/export_model_cache.py
+++ b/scripts/analysis/export_model_cache.py
@@ -101,10 +101,30 @@ def published_path(label, city, out_dir=PUBLISHED_DIR, publish_as=None):
     ``claude-sonnet-5__annapolis.json``, the second silently overwriting the
     first. The cache LABEL must stay the bare model id (it is baked into the
     already-paid cache keys), so the distinguishing name belongs here, at
-    publication time, and nowhere else."""
+    publication time, and nowhere else.
+
+    Callers should prefer ``publication_name`` to fill ``publish_as``: the registry
+    already records every leg's published name, and a flag that has to be typed
+    from memory is a flag that will one day not be."""
     return os.path.join(out_dir, f"{slug(publish_as or label)}__{city}.json")
 
 
+def publication_name(spec, cargs, publish_as=None):
+    """What this leg publishes under: the explicit flag, else the registry, else
+    the plain label.
+
+    Without this, re-exporting a pinned leg and forgetting ``--publish-as`` writes
+    the bare model id — `claude-opus-5__annapolis.json` — which collides with
+    nothing, so the overwrite guard stays quiet, and surfaces only later as a file
+    that belongs to no registered leg. The registry knows the answer; this is the
+    one place that writes the filename, so this is where it should ask.
+    """
+    if publish_as:
+        return publish_as
+    leg = roster.leg_for(spec, cargs)
+    return roster.published_name(leg) if leg is not None else spec_label(spec, cargs)
+
+
 def export(cache_dir, out_dir, splits, specs, allow_partial=False, overrides=None,
            publish_as=None):
     """Consolidate ``.model_cache`` into one file per (model, split).
@@ -137,6 +157,7 @@ def export(cache_dir, out_dir, splits, specs, allow_partial=False, overrides=Non
                          f"several --models specs (got {len(specs)}): every spec "
                          "would write to the same file.")
     for spec in specs:
+        name = publication_name(spec, cargs, publish_as)
         for city in splits:
             bundle = os.path.join(REPO, "benchmark", city)
             if not os.path.exists(os.path.join(bundle, "records.jsonl")):
@@ -162,7 +183,7 @@ def export(cache_dir, out_dir, splits, specs, allow_partial=False, overrides=Non
             if missing and not allow_partial:
                 partial.append((label, city, len(dets), missing))
                 continue
-            path = published_path(label, city, out_dir, publish_as)
+            path = published_path(label, city, out_dir, name)
             # Refuse to overwrite a DIFFERENT leg that happens to share this name.
             # Two legs of one model id (Claude at two effort levels) resolve to the
             # same filename, and a silent overwrite is the worst outcome available:
@@ -175,7 +196,7 @@ def export(cache_dir, out_dir, splits, specs, allow_partial=False, overrides=Non
                     collisions.append((label, city, path))
                     continue
             with open(path, "w", encoding="utf-8") as fh:
-                json.dump({"model": label, "published_as": publish_as or label,
+                json.dump({"model": label, "published_as": name,
                            "city": city, "signature": sig,
                            "n_panos": len(dets), "n_uncached": missing,
                            "detections": dets}, fh, separators=(",", ":"), sort_keys=True)
@@ -202,6 +223,7 @@ def verify(cache_dir, out_dir, splits, specs, overrides=None, publish_as=None):
     rsq = radius_sq_for()
     problems, compared, vacuous, unpublished = [], 0, [], []
     for spec in specs:
+        name = publication_name(spec, cargs, publish_as)
         for city in splits:
             bundle = os.path.join(REPO, "benchmark", city)
             if not os.path.exists(os.path.join(bundle, "records.jsonl")):
@@ -214,7 +236,7 @@ def verify(cache_dir, out_dir, splits, specs, overrides=None, publish_as=None):
             sig = det.signature() if hasattr(det, "signature") else None
             if sig is None:
                 continue
-            pub = load_detections(label, city, out_dir, publish_as)
+            pub = load_detections(label, city, out_dir, name)
             if pub is None:
                 unpublished.append((label, city))
                 continue
diff --git a/scripts/analysis/fp_taxonomy.py b/scripts/analysis/fp_taxonomy.py
index 73bffc0c..7abd4ea2 100644
--- a/scripts/analysis/fp_taxonomy.py
+++ b/scripts/analysis/fp_taxonomy.py
@@ -347,6 +347,12 @@ def main(argv=None):
     radius_sq = radius_sq_for()
     cities = [c.strip() for c in args.cities.split(",") if c.strip()]
     specs = [s.strip() for s in args.models.split(",") if s.strip()]
+    # Build the pool record BEFORE any scoring, not at write time. It raises on an
+    # unregistered or unmeasured model, and raising after every model is scored and
+    # every table is printed throws the whole run away -- and, because it happens
+    # inside the --json-out branch, throws it away only for the runs that were going
+    # to leave an artifact. silent_witness.py validates up front for the same reason.
+    pool = roster.pool_record(specs, cargs)
 
     print(f"=== False-positive taxonomy (#46) — {len(specs)} models x "
           f"{len(cities)} splits ===")
@@ -433,7 +439,7 @@ def main(argv=None):
                        # Which models this ran over, so a reader can tell a roster
                        # change from a numbers change -- the same reasoning as the
                        # detector signature inside each published detections file.
-                       "models": roster.pool_record(specs, cargs),
+                       "models": pool,
                        "per_model": per_model}, fh, indent=2)
         print(f"\nWrote {args.json_out}")
     return 0
diff --git a/scripts/analysis/silent_witness.py b/scripts/analysis/silent_witness.py
index a6222eac..8621af5f 100644
--- a/scripts/analysis/silent_witness.py
+++ b/scripts/analysis/silent_witness.py
@@ -50,17 +50,21 @@
 
 import miss_taxonomy as mt  # noqa: E402
 from miss_decomposition import US_SPLITS  # noqa: E402
-from fp_taxonomy import CHALLENGERS, _compare_args, scaled  # noqa: E402
+from fp_taxonomy import _compare_args, scaled  # noqa: E402
 
 # Sparse = a hit is evidence; dense = a hit is mostly coverage. Both come from the
 # measured densities in docs/model_comparison.md (1-4 boxes/pano at nulls 0.01-0.08,
 # versus the open detectors' 55-88), and the classification lives with the model in
-# rampnet/roster.py rather than in a second tuple here that had to be hand-synced.
-# The split is not a judgement call at the boundary: there is an order of magnitude
-# between the groups. Both are reported; only the sparse group feeds the headline, and
-# the dense group's excess is printed so that choice is checkable rather than asserted.
-SPARSE = roster.SPARSE
-DENSE = roster.DENSE
+# rampnet/roster.py rather than in a second tuple here. The split is not a judgement
+# call at the boundary: there is an order of magnitude between the groups. Both are
+# reported; only the sparse group feeds the headline, and the dense group's excess is
+# printed so that choice is checkable rather than asserted.
+#
+# There is deliberately no module-level SPARSE/DENSE here. This script's pool is
+# WITNESS_POOL_46 by default and whatever --models says otherwise, so a pair of
+# constants bound to the STANDING roster would grow every time a challenger was
+# added while the pool that actually feeds the headline stayed frozen -- naming, at
+# module scope, a set the script does not use. main() partitions its own pool.
 
 
 # --------------------------------------------------------------------------- #
diff --git a/scripts/analysis/size_analysis.py b/scripts/analysis/size_analysis.py
index e656270a..ea96dd27 100644
--- a/scripts/analysis/size_analysis.py
+++ b/scripts/analysis/size_analysis.py
@@ -22,6 +22,7 @@
 sys.path.insert(0, REPO)
 sys.path.insert(0, os.path.join(REPO, "scripts", "model_comparison"))
 
+from rampnet import roster  # noqa: E402
 from rampnet.detection_eval import (
     build_ground_truth, radius_sq_for, PANO_SCALE_X, PANO_SCALE_Y, _xy, prediction_confidence)
 from compare import load_bundle, DetectionCache, cache_key
@@ -33,8 +34,18 @@
 PRO = "gemini-3.1-pro-preview"
 BUCKETS = [(0, 12), (12, 20), (20, 32), (32, 50), (50, 80), (80, 1e9)]
 class Args:
-    gemini_model = PRO; qwen_model = "Qwen/Qwen3-VL-8B-Instruct"
-    qwen_coord_space = "auto"; tiling = "perspective"
+    """The build_detector namespace this script hands in.
+
+    Provider model ids come from the registry rather than being retyped: they feed
+    the detection cache signature, so a literal here that drifts from
+    PROVIDER_DEFAULTS does not crash, it silently misses every cached detection.
+    `gemini_model` is deliberately NOT the registry default -- this analysis is
+    pinned to the pro leg -- which is exactly why it is the one line worth stating.
+    """
+    gemini_model = PRO
+    qwen_model = roster.PROVIDER_DEFAULTS["qwen_model"]
+    qwen_coord_space = roster.PROVIDER_DEFAULTS["qwen_coord_space"]
+    tiling = "perspective"
 
 
 def geom(y):
diff --git a/scripts/model_comparison/compare.py b/scripts/model_comparison/compare.py
index 095a442c..b1e48004 100644
--- a/scripts/model_comparison/compare.py
+++ b/scripts/model_comparison/compare.py
@@ -245,8 +245,12 @@ def _fail_validation(problems):
 ModelRun = namedtuple("ModelRun", ["report", "failures", "scored"])
 
 
+class UnrecordedSpend(Exception):
+    """A paid leg was about to make its first real call with no usage log."""
+
+
 def score_model(detector, records, gts, panos_dir, radius_sq, label, city, cache,
-                max_consecutive_failures=10):
+                max_consecutive_failures=10, spend_needs_recording=False):
     """Run one detector over every scored pano and aggregate the score.
 
     ``gts`` maps pano id -> GroundTruth (verdict-derived for city bundles,
@@ -267,6 +271,19 @@ def score_model(detector, records, gts, panos_dir, radius_sq, label, city, cache
             for pid in gts}
     cached = {pid: (cache.get(k) if k else None) for pid, k in keys.items()}
     if not cached or any(p is None for p in cached.values()):
+        # This leg WILL call the API. If it is a paid one and nothing is recording
+        # the spend, stop here: token counts are the one artifact that cannot be
+        # back-filled -- a later re-run reads the cache, makes zero calls, and can
+        # never reproduce them, which is how the four Claude legs (#122) cost
+        # $28.82 with no committed record. Checked here rather than at parse time
+        # so a fully cached re-score, which cannot spend anything, still runs.
+        if spend_needs_recording and getattr(detector, "name", None) in roster.PAID_PROVIDERS:
+            raise UnrecordedSpend(
+                f"{label} would call a paid API for "
+                f"{sum(1 for p in cached.values() if p is None)} uncached pano(s) with "
+                f"--usage-log none. Token counts cannot be back-filled, so this spend "
+                f"would go unrecorded. Drop --usage-log none, or pass "
+                f"--allow-unrecorded-spend deliberately.")
         detector.prepare()
     else:
         print(f"[{label}] all {len(cached)} panos already cached; model load skipped")
@@ -527,12 +544,15 @@ def write_pr_curves(out_dir, curves):
     print(f"PR curves written to {out_dir} (JSON + {os.path.basename(path)})")
 
 
-def main():
-    # Windows consoles are cp1252; avoid UnicodeEncodeError on stray bytes.
-    for stream in (sys.stdout, sys.stderr):
-        if hasattr(stream, "reconfigure"):
-            stream.reconfigure(errors="replace")
+def build_parser():
+    """The CLI, as one object a test can inspect.
 
+    Extracted from main() so that the coupling between PROVIDER_DEFAULTS and the
+    flags that feed build_detector is checkable rather than asserted in prose:
+    a drift there does not crash, it changes the detection cache key and silently
+    misses every already-paid detection. test_roster.py reads the defaults off
+    this parser.
+    """
     ap = argparse.ArgumentParser(description="Compare curb-ramp detectors on a benchmark bundle.")
     ap.add_argument("bundle", help="Bundle dir (e.g. benchmark/richmond) with records.jsonl + verdicts.json.")
     ap.add_argument("--models", default="rampnet",
@@ -640,6 +660,16 @@ def main():
                     help="Permit a paid model to run with --usage-log none. Needed only "
                          "to spend money without recording what it cost, which is not "
                          "recoverable afterwards; say why in the PR if you use it.")
+    return ap
+
+
+def main():
+    # Windows consoles are cp1252; avoid UnicodeEncodeError on stray bytes.
+    for stream in (sys.stdout, sys.stderr):
+        if hasattr(stream, "reconfigure"):
+            stream.reconfigure(errors="replace")
+
+    ap = build_parser()
     args = ap.parse_args()
 
     load_dotenv(str(REPO_ROOT))
@@ -669,19 +699,11 @@ def main():
     city = os.path.basename(os.path.normpath(args.bundle))
     cache = DetectionCache(args.cache_dir, enabled=not args.no_cache)
     usage_log = None if args.usage_log == "none" else args.usage_log
-    # Fail BEFORE the money is spent, not after. report_usage warns at the end of a
-    # leg that logged nothing, but by then the tokens are bought and the counts are
-    # already unrecoverable: a re-run reads the detection cache, makes zero API
-    # calls, and can never reproduce them. That is exactly how the four Claude legs
-    # (#122) ended up costing $28.82 with no committed record.
-    if usage_log is None and not args.allow_unrecorded_spend:
-        paid = sorted({p for p, _ in specs if p in roster.PAID_PROVIDERS})
-        if paid:
-            ap.error(
-                f"--usage-log none with paid provider(s) {', '.join(paid)}. Token "
-                f"counts cannot be back-filled — a cached re-run makes no API calls — "
-                f"so this would spend money that no committed artifact records. Drop "
-                f"--usage-log none, or pass --allow-unrecorded-spend deliberately.")
+    # Whether a paid leg may run without recording what it spends. The check itself
+    # happens in score_model, at the first pano that is NOT already cached -- still
+    # before any money moves, but without refusing a re-score that provably cannot
+    # spend anything (a fully cached leg skips the model load and makes no calls).
+    spend_needs_recording = usage_log is None and not args.allow_unrecorded_spend
 
     print(f"Bundle: {args.bundle}  ({len(gts)} scored panos)  "
           f"match radius {args.radius}  ground truth: {gt_desc}")
@@ -700,7 +722,13 @@ def main():
         run = None
         try:
             run = score_model(
-                detector, records, gts, panos_dir, radius_sq, label, city, cache)
+                detector, records, gts, panos_dir, radius_sq, label, city, cache,
+                spend_needs_recording=spend_needs_recording)
+        except UnrecordedSpend:
+            # Not a "this model is not runnable here" condition: it is a deliberate
+            # refusal, and swallowing it would let the next paid leg in the list
+            # spend unrecorded too.
+            raise
         except Exception as e:
             # Missing client lib, missing credentials, a checkpoint whose remote
             # code won't load on this transformers version: skip the whole model
diff --git a/scripts/model_comparison/detectors.py b/scripts/model_comparison/detectors.py
index d506df20..0d0148cf 100644
--- a/scripts/model_comparison/detectors.py
+++ b/scripts/model_comparison/detectors.py
@@ -1545,6 +1545,21 @@ def parse_model_spec(token):
     return provider.strip(), (model_id.strip() or None)
 
 
+def _D(key):
+    """One provider default, from the registry.
+
+    build_detector is reached from namespaces that are not compare.py's parser --
+    null_recall and dump_detections build their own, and two analysis scripts hand
+    it a private Args -- so every `getattr(args, k, None) or <literal>` here was a
+    fifth copy of a value that feeds the cache signature. A copy that drifts does
+    not crash; it changes the key and silently misses every already-paid detection.
+    Imported lazily so detectors.py keeps importing without the rampnet package on
+    sys.path.
+    """
+    from rampnet.roster import PROVIDER_DEFAULTS
+    return PROVIDER_DEFAULTS[key]
+
+
 def build_detector(provider, model_id, records, args):
     """Instantiate a detector for one ``(provider, model_id)`` spec, returning
     ``(label, detector)``. The label is the concrete model id for VLMs (so
@@ -1561,8 +1576,8 @@ def build_detector(provider, model_id, records, args):
         mid = model_id or args.claude_model
         return mid, ClaudeDetector(
             model_id=mid, tile=tile,
-            effort=getattr(args, "claude_effort", None) or "low",
-            tool_choice=getattr(args, "claude_tool_choice", None) or "auto",
+            effort=getattr(args, "claude_effort", None) or _D("claude_effort"),
+            tool_choice=getattr(args, "claude_tool_choice", None) or _D("claude_tool_choice"),
             image_format=(getattr(args, "claude_image_format", None)
                           or CLAUDE_AS_RUN_IMAGE_FORMAT),
             temperature=getattr(args, "claude_temperature", CLAUDE_AS_RUN_TEMPERATURE))
@@ -1572,18 +1587,18 @@ def build_detector(provider, model_id, records, args):
         return mid, QwenDetector(model_id=mid, tile=tile,
                                  coord_space=None if coord_space == "auto" else coord_space)
     if provider == "owlv2":
-        mid = model_id or getattr(args, "owlv2_model", None) or "google/owlv2-large-patch14-ensemble"
+        mid = model_id or getattr(args, "owlv2_model", None) or _D("owlv2_model")
         return mid, OwlV2Detector(model_id=mid, tile=tile,
                                   query=getattr(args, "owlv2_query", None),
                                   score_threshold=getattr(args, "score_threshold", None))
     if provider == "gdino":
-        mid = model_id or getattr(args, "gdino_model", None) or "IDEA-Research/grounding-dino-base"
+        mid = model_id or getattr(args, "gdino_model", None) or _D("gdino_model")
         return mid, GroundingDinoDetector(model_id=mid, tile=tile,
                                           query=getattr(args, "gdino_query", None),
                                           score_threshold=getattr(args, "score_threshold", None),
                                           text_threshold=getattr(args, "gdino_text_threshold", None))
     if provider == "molmo":
-        mid = model_id or getattr(args, "molmo_model", None) or "allenai/Molmo2-8B"
+        mid = model_id or getattr(args, "molmo_model", None) or _D("molmo_model")
         scale = getattr(args, "molmo_coord_scale", "auto")
         return mid, MolmoDetector(model_id=mid, tile=tile,
                                   coord_scale=None if scale in (None, "auto") else float(scale))
@@ -1596,10 +1611,11 @@ def build_detector(provider, model_id, records, args):
                              "--models yolo:<path.pt> or --yolo-model <path.pt>")
         iou = getattr(args, "yolo_iou", None)
         imgsz = getattr(args, "yolo_imgsz", None)
+        iou = _D("yolo_iou") if iou is None else float(iou)
+        imgsz = _D("yolo_imgsz") if imgsz is None else int(imgsz)
         label = os.path.splitext(os.path.basename(str(weights)))[0]
         return label, YoloDetector(weights=weights, label=label, tile=tile,
                                    conf=getattr(args, "yolo_conf", None),
-                                   iou=0.5 if iou is None else float(iou),
-                                   imgsz=1024 if imgsz is None else int(imgsz))
+                                   iou=iou, imgsz=imgsz)
     raise ValueError(f"unknown provider '{provider}' "
                      f"(choose from: {', '.join(PROVIDERS)})")
diff --git a/tests/test_export_model_cache.py b/tests/test_export_model_cache.py
index 4622458a..690889e8 100644
--- a/tests/test_export_model_cache.py
+++ b/tests/test_export_model_cache.py
@@ -226,7 +226,9 @@ def test_export_refuses_to_overwrite_a_different_leg(tmp_path, monkeypatch):
     the other leg's numbers are simply gone."""
     out = tmp_path / "out"
     out.mkdir()
-    existing = out / "claude-sonnet-5__annapolis.json"
+    # The name the low-effort leg publishes under, per the registry -- not the bare
+    # model id, which no longer collides because publication_name resolves it.
+    existing = out / "claude-sonnet-5-effort-low__annapolis.json"
     existing.write_text(json.dumps({
         "model": "claude-sonnet-5", "city": "annapolis",
         "signature": {"provider": "claude", "effort": "high"},
@@ -247,7 +249,7 @@ def test_export_overwrites_the_same_leg_happily(tmp_path, monkeypatch):
     out = tmp_path / "out"
     out.mkdir()
     sig = {"provider": "claude", "effort": "low"}
-    (out / "claude-sonnet-5__annapolis.json").write_text(json.dumps({
+    (out / "claude-sonnet-5-effort-low__annapolis.json").write_text(json.dumps({
         "model": "claude-sonnet-5", "city": "annapolis", "signature": sig,
         "detections": {"p1": []}}), encoding="utf-8")
 
@@ -256,6 +258,23 @@ def test_export_overwrites_the_same_leg_happily(tmp_path, monkeypatch):
     assert collisions == [] and len(written) == 1
 
 
+def test_a_pinned_leg_publishes_under_its_registry_name_without_being_told():
+    """--publish-as used to be the only thing standing between a pinned leg and the
+    bare model id. Forgetting it wrote claude-opus-5__annapolis.json, which collides
+    with no existing file, so the overwrite guard stayed quiet and it surfaced only
+    later as a file belonging to no registered leg. The registry knows the name."""
+    cargs = em._compare_args(".model_cache")
+    cargs.claude_effort = "high"
+    assert em.publication_name("claude:claude-opus-5", cargs) == "claude-opus-5-effort-high"
+    cargs.claude_effort = "low"
+    assert em.publication_name("claude:claude-opus-5", cargs) == "claude-opus-5-effort-low"
+    # An explicit flag still wins -- it is how an unregistered leg gets a name.
+    assert em.publication_name("claude:claude-opus-5", cargs, "other") == "other"
+    # And an unregistered spec falls back to its plain label rather than raising:
+    # naming a file is not the place to enforce registration.
+    assert em.publication_name("gemini:gemini-9-turbo", cargs) == "gemini-9-turbo"
+
+
 def test_publish_as_refuses_more_than_one_spec(tmp_path):
     with pytest.raises(ValueError, match="ONE leg"):
         em.export("/nope", str(tmp_path), ["annapolis"],
diff --git a/tests/test_model_comparison.py b/tests/test_model_comparison.py
index 29d735b1..da3b7e75 100644
--- a/tests/test_model_comparison.py
+++ b/tests/test_model_comparison.py
@@ -29,6 +29,7 @@
 from dump_detections import detections_to_view_shapes  # noqa: E402
 
 
+import compare  # noqa: E402
 from compare import (  # noqa: E402
     score_model, validate_bundle, validate_manual_bundle, DetectionCache, cache_key,
     ground_truths_from_verdicts, has_confidences, load_bundle,
@@ -1256,49 +1257,77 @@ def test_a_paid_leg_with_the_usage_log_disabled_says_so_loudly(capsys):
     assert "WARNING" in out and "not recorded" in out.lower()
 
 
-# --- ... and the run refuses to start in the first place --------------------
-
-def _run_compare(argv, monkeypatch):
-    """Invoke compare.main() as the CLI would, returning (SystemExit code, stderr)."""
-    import compare
-    monkeypatch.setattr(sys, "argv", ["compare.py"] + argv)
-    with pytest.raises(SystemExit) as exc:
-        compare.main()
-    return exc.value.code
+# --- ... and the run stops before the first uncached call -------------------
 
+class _PaidDetector(_UnloadableDetector):
+    """A paid provider that cannot load — so any test that reaches prepare() fails
+    loudly instead of quietly reaching for the network."""
+    name = "claude"
 
-@pytest.mark.parametrize("spec", ["claude:claude-opus-5", "gemini:gemini-3.6-flash",
-                                  "rampnet,claude:claude-sonnet-5"])
-def test_a_paid_run_refuses_to_start_with_the_usage_log_disabled(spec, monkeypatch,
-                                                                 capsys):
-    """The warning in report_usage fires AFTER the tokens are bought, which is too
-    late for the one artifact that cannot be back-filled. This fires before."""
-    code = _run_compare([os.path.join(REPO_ROOT, "benchmark", "annapolis"), "--models", spec,
-                         "--usage-log", "none"], monkeypatch)
-    assert code != 0
-    err = capsys.readouterr().err
-    assert "--usage-log none" in err and "back-filled" in err
 
-
-def test_a_free_model_may_run_without_a_usage_log(monkeypatch):
-    """The check is about spend, not about logging for its own sake. A local model
-    costs nothing, so requiring a spend record from it would be noise."""
-    import compare
-    monkeypatch.setattr(sys, "argv", ["compare.py", os.path.join(REPO_ROOT, "benchmark", "annapolis"),
-                                      "--models", "rampnet", "--usage-log", "none",
-                                      "--limit", "1"])
-    compare.main()          # must not raise SystemExit
+def _aligned_gts():
+    records, verdicts = _aligned()
+    return records, ground_truths_from_verdicts(records, verdicts)
+
+
+def test_a_paid_leg_stops_before_its_first_uncached_call(tmp_path):
+    """The end-of-run warning fires after the tokens are bought. This fires before
+    the first one, and before prepare() — _PaidDetector raises from prepare(), so a
+    guard that let the run through would surface as ImportError, not as this."""
+    records, gts = _aligned_gts()
+    with pytest.raises(compare.UnrecordedSpend) as exc:
+        score_model(_PaidDetector(), records, gts, "", radius_sq_for(),
+                    "claude-opus-5", "richmond", DetectionCache(str(tmp_path)),
+                    spend_needs_recording=True)
+    assert "uncached pano" in str(exc.value) and "--usage-log none" in str(exc.value)
+
+
+def test_a_fully_cached_paid_leg_still_runs(tmp_path):
+    """It provably cannot spend: every pano is cached, so the model is never loaded
+    and no call is made. Refusing it would block re-scoring the published detections
+    from a clean clone, which is the path the roster exists to keep open."""
+    records, gts = _aligned_gts()
+    det = _PaidDetector()
+    cache = DetectionCache(str(tmp_path))
+    cache.put(cache_key("claude-opus-5", det.signature(), "richmond", "p1"),
+              [(0.1, 0.1, None)])
+    run = score_model(det, records, gts, "", radius_sq_for(), "claude-opus-5",
+                      "richmond", cache, spend_needs_recording=True)
+    assert run.report.n_panos == 1 and not run.failures
 
 
-def test_unrecorded_spend_stays_possible_but_deliberate(monkeypatch):
-    """A guard with no override gets worked around by editing it out, which is
-    worse. The override is a named flag, so using it is visible in the command."""
-    import compare
-    monkeypatch.setattr(sys, "argv", ["compare.py", os.path.join(REPO_ROOT, "benchmark", "annapolis"),
-                                      "--models", "claude:claude-opus-5",
-                                      "--usage-log", "none", "--allow-unrecorded-spend",
-                                      "--limit", "1"])
-    compare.main()          # reaches the run; the leg itself is "not runnable" here
+def test_a_free_model_may_run_unrecorded(tmp_path):
+    """The rule is about spend, not about logging for its own sake."""
+    records, gts = _aligned_gts()
+    with pytest.raises(ImportError):        # reached prepare(), i.e. was not refused
+        score_model(_UnloadableDetector(), records, gts, "", radius_sq_for(),
+                    "unloadable", "richmond", DetectionCache(str(tmp_path)),
+                    spend_needs_recording=True)
+
+
+def test_unrecorded_spend_stays_possible_but_deliberate(tmp_path):
+    """A guard with no override gets edited out instead, which is worse. With
+    --allow-unrecorded-spend the run proceeds — here, as far as prepare()."""
+    records, gts = _aligned_gts()
+    with pytest.raises(ImportError):
+        score_model(_PaidDetector(), records, gts, "", radius_sq_for(),
+                    "claude-opus-5", "richmond", DetectionCache(str(tmp_path)),
+                    spend_needs_recording=False)
+
+
+def test_the_refusal_is_not_swallowed_as_an_unrunnable_model(monkeypatch, capsys):
+    """main() skips a model that cannot run here, with a printed note. The refusal
+    must NOT take that path — swallowing it would let the next paid leg in the same
+    --models list spend unrecorded too."""
+    def _refuse(*a, **kw):
+        raise compare.UnrecordedSpend("would spend")
+    monkeypatch.setattr(compare, "score_model", _refuse)
+    monkeypatch.setattr(sys, "argv", ["compare.py",
+                                      os.path.join(REPO_ROOT, "benchmark", "richmond"),
+                                      "--models", "rampnet", "--usage-log", "none"])
+    with pytest.raises(compare.UnrecordedSpend):
+        compare.main()
+    assert "not runnable" not in capsys.readouterr().out
 
 
 def test_the_paid_provider_list_covers_every_priced_model():
diff --git a/tests/test_roster.py b/tests/test_roster.py
index 6cfc7523..0fa7fc2f 100644
--- a/tests/test_roster.py
+++ b/tests/test_roster.py
@@ -93,12 +93,30 @@ def test_no_doc_still_hardcodes_the_old_roster_count():
     and passes while the docs are still wrong.
     """
     import re
-    stale = ("all 8", "8-model roster", "seven-model roster", "all 8 model groups",
-             "8 model groups")
-    for name in ("model_comparison.md", "replication.md", "curb_ramp_data_sourcing.md"):
+    # Each entry is a phrase that was actually in the docs and wrong. Two properties
+    # matter and neither is obvious:
+    #  * No entry may be a prefix of another -- "all 8" and "all 8 model groups"
+    #    both shipped, and the shorter can never fail independently, so the longer
+    #    reads as coverage it does not add.
+    #  * The count has to be bound to the roster, or the guard fires on perfectly
+    #    good prose. "all 8" alone would reject a future "all 8 splits"; the splits
+    #    are a different axis and there are ten of them.
+    stale = (r"all 8 (?:model|challenger|zero-shot)", r"all 8(?! splits| cities)",
+             r"8-model roster", r"seven-model roster", r"8 model groups")
+    docs = ("model_comparison.md", "replication.md", "curb_ramp_data_sourcing.md")
+    for name in docs:
         text = re.sub(r"\s+", " ", (REPO / "docs" / name).read_text("utf-8"))
         for phrase in stale:
-            assert phrase not in text, f"docs/{name} still says {phrase!r}"
+            hit = re.search(phrase, text)
+            assert hit is None, f"docs/{name} still says {hit.group(0)!r}"
+    # The analysis README carries per-model prose and this PR edits it, so it is in
+    # scope for the same rot even though it is not under docs/.
+    readme = REPO / "scripts" / "analysis" / "README.md"
+    if readme.exists():
+        text = re.sub(r"\s+", " ", readme.read_text("utf-8"))
+        for phrase in stale:
+            hit = re.search(phrase, text)
+            assert hit is None, f"scripts/analysis/README.md still says {hit.group(0)!r}"
 
 
 # --------------------------------------------------------------------------- #
@@ -208,7 +226,7 @@ def test_every_registered_leg_has_published_detections():
     """The other direction. An entry with no files is a model someone meant to run,
     or a name that drifted from the filename it is supposed to predict."""
     missing = [roster.published_name(c) for c in roster.PUBLISHED
-               if not list(DETECTIONS.glob(roster.slug(roster.published_name(c)) + "__*.json"))]
+               if not list(DETECTIONS.glob(roster.published_filename(c, "*")))]
     assert not missing, "registered but nothing published: " + ", ".join(missing)
 
 
@@ -222,9 +240,9 @@ def test_each_published_file_names_the_leg_it_says_it_is():
     """The filename, the `published_as` recorded inside, and the registry all have to
     agree, or a file can be renamed into a different leg's identity."""
     for name in _published_files():
-        stem, _, _ = name.rpartition("__")
+        city = name.rpartition("__")[2][:-len(".json")]
         entry = next((c for c in roster.ROSTER
-                      if roster.slug(roster.published_name(c)) == stem), None)
+                      if roster.published_filename(c, city) == name), None)
         assert entry is not None, name
         payload = json.loads((DETECTIONS / name).read_text("utf-8"))
         assert payload["model"] == entry.label, name
@@ -319,9 +337,10 @@ def test_provider_defaults_match_compare_pys_parser():
     sys.path.insert(0, str(REPO / "scripts" / "model_comparison"))
     import compare  # noqa: E402
 
-    parser = compare.build_parser() if hasattr(compare, "build_parser") else None
-    if parser is None:
-        pytest.skip("compare.py builds its parser inline inside main()")
-    defaults = {a.dest: a.default for a in parser._actions}
+    # Deliberately not guarded by hasattr(): this test spent its whole life skipping
+    # because compare.py built its parser inline, so it read as coverage of the most
+    # load-bearing invariant here while asserting nothing. If build_parser goes away,
+    # this must fail, not skip.
+    defaults = {a.dest: a.default for a in compare.build_parser()._actions}
     for key, value in roster.PROVIDER_DEFAULTS.items():
         assert defaults[key] == value, key
diff --git a/tests/test_silent_witness.py b/tests/test_silent_witness.py
index 076de10b..746dc604 100644
--- a/tests/test_silent_witness.py
+++ b/tests/test_silent_witness.py
@@ -152,13 +152,19 @@ def test_summarize_reports_the_population_size():
 # --------------------------------------------------------------------------- #
 # bookkeeping — the sparse/dense split is load-bearing
 # --------------------------------------------------------------------------- #
-def test_sparse_and_dense_partition_the_roster():
-    from fp_taxonomy import CHALLENGERS
-    assert set(sw.SPARSE) | set(sw.DENSE) == set(CHALLENGERS)
-    assert set(sw.SPARSE) & set(sw.DENSE) == set()
+def test_the_frozen_pool_partitions_into_sparse_and_dense():
+    """The partition that matters is the one over the pool the script actually runs,
+    not over the standing roster: those two can differ, which is the whole point of
+    the freeze. (The roster-wide partition is covered in tests/test_roster.py.)"""
+    from rampnet import roster
+    sparse, dense = roster.partition_by_density(roster.WITNESS_POOL_46)
+    assert set(sparse) | set(dense) == set(roster.WITNESS_POOL_46)
+    assert not set(sparse) & set(dense)
 
 
 def test_the_open_vocabulary_detectors_are_the_dense_ones():
     # They are the models docs/model_comparison.md measures at 55-88 boxes/pano, and
     # the headline deliberately excludes them: at that density a witness is free.
-    assert set(sw.DENSE) == {"owlv2", "gdino"}
+    from rampnet import roster
+    _, dense = roster.partition_by_density(roster.WITNESS_POOL_46)
+    assert set(dense) == {"owlv2", "gdino"}

From ca9275a03ec2fae128f1f182b0b34505a8fa988e Mon Sep 17 00:00:00 2001
From: Jon Froehlich <jonf@cs.uw.edu>
Date: Tue, 18 Aug 2026 13:32:13 -0700
Subject: [PATCH 7/7] Bring the published detections into canonical form,
 without a cache (#122)

108 of the 114 files in benchmark/model_detections/ were exported before the
`published_as` field existed, so re-running the exporter on any of them produced
a file that differed from the committed one -- identical detections, different
envelope. docs/replication.md promises that a derived artifact can be PROVEN
identical when regenerated, and that was not true of 95% of this corpus.

I first assumed closing it meant re-exporting from .model_cache, i.e. finding
the machine that produced each leg -- Hyak for the open detectors, makelab2 for
the YOLO trio. It does not. The serialization is deterministic (now DUMP_KW, one
definition), all 114 files round-trip byte-identically through it, and for every
one of these the published name is recoverable from the file itself, so the
result is exactly what a real re-export would write.

  python scripts/analysis/export_model_cache.py --canonicalize [--write]

Cache-free, detections untouched, and it REFUSES rather than guesses when a
file's published name cannot be derived from its contents -- guessing there is
the silent rename this mechanism exists to prevent. Measured on the corpus: 108
files rewritten, 0 detections changed, `published_as` the only key that differs.

Three tests keep it shut: every file equals its own canonical re-dump, every
file declares the name it is published under and agrees with its filename, and
canonicalize cannot alter a detection.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
---
 ...earch__grounding-dino-base__annapolis.json |  2 +-
 ...A-Research__grounding-dino-base__bend.json |  2 +-
 ...ounding-dino-base__budapest_district5.json |  2 +-
 ...Research__grounding-dino-base__clovis.json |  2 +-
 ...rch__grounding-dino-base__gainesville.json |  2 +-
 ...rch__grounding-dino-base__manual_gold.json |  2 +-
 ...arch__grounding-dino-base__morgantown.json |  2 +-
 ...search__grounding-dino-base__paterson.json |  2 +-
 ...search__grounding-dino-base__richmond.json |  2 +-
 ...earch__grounding-dino-base__sao_paulo.json |  2 +-
 ...wen__Qwen3-VL-32B-Instruct__annapolis.json |  2 +-
 .../Qwen__Qwen3-VL-32B-Instruct__bend.json    |  2 +-
 ...3-VL-32B-Instruct__budapest_district5.json |  2 +-
 .../Qwen__Qwen3-VL-32B-Instruct__clovis.json  |  2 +-
 ...n__Qwen3-VL-32B-Instruct__gainesville.json |  2 +-
 ...n__Qwen3-VL-32B-Instruct__manual_gold.json |  2 +-
 ...en__Qwen3-VL-32B-Instruct__morgantown.json |  2 +-
 ...Qwen__Qwen3-VL-32B-Instruct__paterson.json |  2 +-
 ...Qwen__Qwen3-VL-32B-Instruct__richmond.json |  2 +-
 ...wen__Qwen3-VL-32B-Instruct__sao_paulo.json |  2 +-
 ...Qwen__Qwen3-VL-8B-Instruct__annapolis.json |  2 +-
 .../Qwen__Qwen3-VL-8B-Instruct__bend.json     |  2 +-
 ...n3-VL-8B-Instruct__budapest_district5.json |  2 +-
 .../Qwen__Qwen3-VL-8B-Instruct__clovis.json   |  2 +-
 ...en__Qwen3-VL-8B-Instruct__gainesville.json |  2 +-
 ...en__Qwen3-VL-8B-Instruct__manual_gold.json |  2 +-
 ...wen__Qwen3-VL-8B-Instruct__morgantown.json |  2 +-
 .../Qwen__Qwen3-VL-8B-Instruct__paterson.json |  2 +-
 .../Qwen__Qwen3-VL-8B-Instruct__richmond.json |  2 +-
 ...Qwen__Qwen3-VL-8B-Instruct__sao_paulo.json |  2 +-
 .../allenai__Molmo2-8B__annapolis.json        |  2 +-
 .../allenai__Molmo2-8B__bend.json             |  2 +-
 ...llenai__Molmo2-8B__budapest_district5.json |  2 +-
 .../allenai__Molmo2-8B__clovis.json           |  2 +-
 .../allenai__Molmo2-8B__gainesville.json      |  2 +-
 .../allenai__Molmo2-8B__manual_gold.json      |  2 +-
 .../allenai__Molmo2-8B__morgantown.json       |  2 +-
 .../allenai__Molmo2-8B__paterson.json         |  2 +-
 .../allenai__Molmo2-8B__richmond.json         |  2 +-
 .../allenai__Molmo2-8B__sao_paulo.json        |  2 +-
 .../gemini-3.1-pro-preview__annapolis.json    |  2 +-
 .../gemini-3.1-pro-preview__bend.json         |  2 +-
 ...i-3.1-pro-preview__budapest_district5.json |  2 +-
 .../gemini-3.1-pro-preview__clovis.json       |  2 +-
 .../gemini-3.1-pro-preview__gainesville.json  |  2 +-
 .../gemini-3.1-pro-preview__morgantown.json   |  2 +-
 .../gemini-3.1-pro-preview__paterson.json     |  2 +-
 .../gemini-3.1-pro-preview__richmond.json     |  2 +-
 .../gemini-3.1-pro-preview__sao_paulo.json    |  2 +-
 .../gemini-3.6-flash__annapolis.json          |  2 +-
 .../gemini-3.6-flash__bend.json               |  2 +-
 .../gemini-3.6-flash__budapest_district5.json |  2 +-
 .../gemini-3.6-flash__clovis.json             |  2 +-
 .../gemini-3.6-flash__gainesville.json        |  2 +-
 .../gemini-3.6-flash__morgantown.json         |  2 +-
 .../gemini-3.6-flash__paterson.json           |  2 +-
 .../gemini-3.6-flash__richmond.json           |  2 +-
 .../gemini-3.6-flash__sao_paulo.json          |  2 +-
 .../gemini-3.7-flash__annapolis.json          |  2 +-
 .../gemini-3.7-flash__bend.json               |  2 +-
 .../gemini-3.7-flash__budapest_district5.json |  2 +-
 .../gemini-3.7-flash__clovis.json             |  2 +-
 .../gemini-3.7-flash__gainesville.json        |  2 +-
 .../gemini-3.7-flash__manual_gold.json        |  2 +-
 .../gemini-3.7-flash__morgantown.json         |  2 +-
 .../gemini-3.7-flash__paterson.json           |  2 +-
 .../gemini-3.7-flash__richmond.json           |  2 +-
 .../gemini-3.7-flash__sao_paulo.json          |  2 +-
 ...lv2-large-patch14-ensemble__annapolis.json |  2 +-
 ...e__owlv2-large-patch14-ensemble__bend.json |  2 +-
 ...-patch14-ensemble__budapest_district5.json |  2 +-
 ..._owlv2-large-patch14-ensemble__clovis.json |  2 +-
 ...2-large-patch14-ensemble__gainesville.json |  2 +-
 ...2-large-patch14-ensemble__manual_gold.json |  2 +-
 ...v2-large-patch14-ensemble__morgantown.json |  2 +-
 ...wlv2-large-patch14-ensemble__paterson.json |  2 +-
 ...wlv2-large-patch14-ensemble__richmond.json |  2 +-
 ...lv2-large-patch14-ensemble__sao_paulo.json |  2 +-
 .../y11l_pano__annapolis.json                 |  2 +-
 .../model_detections/y11l_pano__bend.json     |  2 +-
 .../y11l_pano__budapest_district5.json        |  2 +-
 .../model_detections/y11l_pano__clovis.json   |  2 +-
 .../y11l_pano__gainesville.json               |  2 +-
 .../y11l_pano__manual_gold.json               |  2 +-
 .../y11l_pano__morgantown.json                |  2 +-
 .../model_detections/y11l_pano__paterson.json |  2 +-
 .../model_detections/y11l_pano__richmond.json |  2 +-
 .../y11l_pano__sao_paulo.json                 |  2 +-
 .../y11x_pano_h200__annapolis.json            |  2 +-
 .../y11x_pano_h200__bend.json                 |  2 +-
 .../y11x_pano_h200__budapest_district5.json   |  2 +-
 .../y11x_pano_h200__clovis.json               |  2 +-
 .../y11x_pano_h200__gainesville.json          |  2 +-
 .../y11x_pano_h200__manual_gold.json          |  2 +-
 .../y11x_pano_h200__morgantown.json           |  2 +-
 .../y11x_pano_h200__paterson.json             |  2 +-
 .../y11x_pano_h200__richmond.json             |  2 +-
 .../y11x_pano_h200__sao_paulo.json            |  2 +-
 .../model_detections/y26_pano__annapolis.json |  2 +-
 .../model_detections/y26_pano__bend.json      |  2 +-
 .../y26_pano__budapest_district5.json         |  2 +-
 .../model_detections/y26_pano__clovis.json    |  2 +-
 .../y26_pano__gainesville.json                |  2 +-
 .../y26_pano__manual_gold.json                |  2 +-
 .../y26_pano__morgantown.json                 |  2 +-
 .../model_detections/y26_pano__paterson.json  |  2 +-
 .../model_detections/y26_pano__richmond.json  |  2 +-
 .../model_detections/y26_pano__sao_paulo.json |  2 +-
 docs/replication.md                           | 23 ++++++-
 scripts/analysis/export_model_cache.py        | 68 ++++++++++++++++++-
 tests/test_export_model_cache.py              | 44 ++++++++++++
 111 files changed, 240 insertions(+), 111 deletions(-)

diff --git a/benchmark/model_detections/IDEA-Research__grounding-dino-base__annapolis.json b/benchmark/model_detections/IDEA-Research__grounding-dino-base__annapolis.json
index 451ceca4..68031588 100644
--- a/benchmark/model_detections/IDEA-Research__grounding-dino-base__annapolis.json
+++ b/benchmark/model_detections/IDEA-Research__grounding-dino-base__annapolis.json
@@ -1 +1 @@
-{"city":"annapolis","detections":{"1005430537402761":[[0.16291370316442239,0.590038592515497,0.4831617474555969],[0.41883495547421756,0.5577300233000989,0.43588986992836],[0.3729743636275448,0.5522631026357258,0.3588933050632477],[0.8894678598135431,0.5551447559027832,0.35182613134384155],[0.22470662865580487,0.5712143515394434,0.35082241892814636],[0.6168658358470661,0.570570424966295,0.34657391905784607],[0.10682195543650175,0.6074872022613815,0.32153525948524475],[0.999929872458069,0.7925127348431653,0.31906506419181824],[0.7256712502445053,0.5595678114090036,0.30421361327171326],[0.03558957483370817,0.5563803011307511,0.2964244484901428],[0.6664656967540816,0.8328084482773205,0.2917221188545227],[0.6763003138228469,0.5554000079785077,0.28314173221588135],[0.0750252777645894,0.5768567696297618,0.28272175788879395],[0.8333316485176208,0.8067323333562464,0.27906325459480286],[0.3332715343737093,0.8333441062653892,0.26574307680130005],[0.18811919348744144,0.5883044112202467,0.26129794120788574],[0.49998607786957067,0.8331103483788824,0.24082425236701965],[0.9123102542903909,0.5553836936828391,0.22421596944332123],[0.1390352705514502,0.5962239297909329,0.21516931056976318],[0.5731773679851184,0.542285390177426,0.21266542375087738],[0.1667260744598989,0.8054984978452466,0.20598983764648438],[0.4469900065880589,0.5487595051393941,0.19466622173786163],[0.6542466424014248,0.5843428203155695,0.19138412177562714],[0.25293520179504175,0.5330768096281442,0.16968055069446564],[0.30990227719895214,0.5168876642758687,0.1644858717918396],[0.008573089704613845,0.8644530399579868,0.14433163404464722],[0.8530170598212243,0.5564465498146052,0.13667508959770203],[0.33324259439804305,0.7367717984055848,0.12008049339056015],[0.8374126053063538,0.865806605940877,0.11788574606180191],[0.999981026773168,0.7416695949701191,0.11261831969022751],[0.8332947587905304,0.7324892063768755,0.10797431319952011],[0.7722785748009005,0.801839376338245,0.10589250922203064],[0.9404494723741945,0.5671946844496172,0.10027828067541122],[0.35857245036866014,0.83262608897343,0.09932075440883636],[0.49989386862324675,0.7204291637288761,0.09919624030590057],[0.6385067276914997,0.542640823794746,0.09332936257123947],[0.6558478098179374,0.5023353775356668,0.08729147911071777],[0.0976309505077585,0.7613541599390063,0.0867684856057167],[0.28693571697363995,0.5117004891109568,0.08267569541931152],[0.3315720932119448,0.5373006093139074,0.07466208189725876],[0.16665449289884116,0.7582410936986905,0.07393774390220642],[0.8135006770303743,0.8650210863851926,0.07342307269573212],[0.5008921967034295,0.5525306641010188,0.07302816212177277],[0.15443353204040333,0.8640181252499837,0.0699392780661583],[0.05045218140226587,0.5931036887964856,0.06992065906524658],[0.14039552811158806,0.7266646013337894,0.06899077445268631],[0.8852609940245022,0.4903777943070585,0.06439677625894547],[0.7108735591925188,0.633588397844926,0.06343699246644974],[0.7368779009062516,0.7815033950995012,0.06330864876508713],[0.6665473346928077,0.7229562877986561,0.061652883887290955],[0.8301552720158211,0.5263997402956403,0.059549883008003235],[0.42280275956943225,0.5087822938694245,0.05825115367770195],[0.46364720412702337,0.7768783955023006,0.05621537193655968],[0.47071594204897593,0.5349907893237582,0.0542498379945755],[0.6812530451026936,0.471079657222115,0.05240100249648094],[0.05140780128233369,0.7836207458626706,0.05126452073454857]],"1018302322713012":[[0.6666304115578308,0.831330006215752,0.4214595556259155],[0.9996926906767416,0.7925472270202856,0.4143754243850708],[0.8333419119783585,0.8071786167270014,0.3913531005382538],[0.1666047520929269,0.8077161753728014,0.36408472061157227],[0.5001646698655122,0.8330987395642981,0.3384704887866974],[0.4235872946167464,0.5591392506554196,0.3356774151325226],[0.07113396630764135,0.5408377791516406,0.33287015557289124],[0.2793944312653427,0.5746295499643645,0.32702434062957764],[0.38550746590109175,0.5796897729580924,0.30824828147888184],[0.8801712967918534,0.5408550206758074,0.3063790798187256],[0.7061021377346121,0.5442704083074745,0.3029841184616089],[0.3602177184353082,0.5663478098387159,0.2866073548793793],[0.33375738480150097,0.8312718366682326,0.2536258399486542],[0.4999579708753911,0.7193324585456612,0.2358810156583786],[0.6541189938141649,0.5439405094277603,0.2345878928899765],[0.8384746209570608,0.8654689413872445,0.20054078102111816],[0.00798024779635903,0.8642963825500061,0.196181058883667],[0.2937224968817366,0.8001051101528556,0.19192934036254883],[0.9156150090949173,0.5462569014507774,0.1889220029115677],[0.2903387581936652,0.6200420800458152,0.1630157083272934],[0.1236771389485069,0.546647055648819,0.16225296258926392],[0.17274454199151135,0.8639407657574281,0.15722166001796722],[0.16653684471724634,0.7384433920980402,0.14952358603477478],[0.33325030806543754,0.7402836168585479,0.1450340300798416],[0.5946331469351506,0.517790975200195,0.13845279812812805],[0.8323351465873071,0.5441260280298029,0.13698922097682953],[0.76123867489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\ No newline at end of file
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\ No newline at end of file
diff --git a/benchmark/model_detections/IDEA-Research__grounding-dino-base__bend.json b/benchmark/model_detections/IDEA-Research__grounding-dino-base__bend.json
index 66fe7f12..861f50f3 100644
--- a/benchmark/model_detections/IDEA-Research__grounding-dino-base__bend.json
+++ b/benchmark/model_detections/IDEA-Research__grounding-dino-base__bend.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/IDEA-Research__grounding-dino-base__budapest_district5.json b/benchmark/model_detections/IDEA-Research__grounding-dino-base__budapest_district5.json
index 3c5ac981..b10f7296 100644
--- a/benchmark/model_detections/IDEA-Research__grounding-dino-base__budapest_district5.json
+++ b/benchmark/model_detections/IDEA-Research__grounding-dino-base__budapest_district5.json
@@ -1 +1 @@
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\ No newline at end of file
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\ No newline at end of file
diff --git a/benchmark/model_detections/IDEA-Research__grounding-dino-base__clovis.json b/benchmark/model_detections/IDEA-Research__grounding-dino-base__clovis.json
index 65823165..3a0f6cf1 100644
--- a/benchmark/model_detections/IDEA-Research__grounding-dino-base__clovis.json
+++ b/benchmark/model_detections/IDEA-Research__grounding-dino-base__clovis.json
@@ -1 +1 @@
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\ No newline at end of file
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\ No newline at end of file
diff --git a/benchmark/model_detections/IDEA-Research__grounding-dino-base__gainesville.json b/benchmark/model_detections/IDEA-Research__grounding-dino-base__gainesville.json
index 2e80fe5f..c50ec3a0 100644
--- a/benchmark/model_detections/IDEA-Research__grounding-dino-base__gainesville.json
+++ b/benchmark/model_detections/IDEA-Research__grounding-dino-base__gainesville.json
@@ -1 +1 @@
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\ No newline at end of file
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\ No newline at end of file
diff --git a/benchmark/model_detections/IDEA-Research__grounding-dino-base__manual_gold.json b/benchmark/model_detections/IDEA-Research__grounding-dino-base__manual_gold.json
index 983b76b3..8af640de 100644
--- a/benchmark/model_detections/IDEA-Research__grounding-dino-base__manual_gold.json
+++ b/benchmark/model_detections/IDEA-Research__grounding-dino-base__manual_gold.json
@@ -1 +1 @@
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\ No newline at end of file
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\ No newline at end of file
diff --git a/benchmark/model_detections/IDEA-Research__grounding-dino-base__morgantown.json b/benchmark/model_detections/IDEA-Research__grounding-dino-base__morgantown.json
index 470bbdcf..a9311ff8 100644
--- a/benchmark/model_detections/IDEA-Research__grounding-dino-base__morgantown.json
+++ b/benchmark/model_detections/IDEA-Research__grounding-dino-base__morgantown.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/IDEA-Research__grounding-dino-base__paterson.json b/benchmark/model_detections/IDEA-Research__grounding-dino-base__paterson.json
index 98b9b162..e16e19c5 100644
--- a/benchmark/model_detections/IDEA-Research__grounding-dino-base__paterson.json
+++ b/benchmark/model_detections/IDEA-Research__grounding-dino-base__paterson.json
@@ -1 +1 @@
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\ No newline at end of file
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\ No newline at end of file
diff --git a/benchmark/model_detections/IDEA-Research__grounding-dino-base__richmond.json b/benchmark/model_detections/IDEA-Research__grounding-dino-base__richmond.json
index cc16f7da..18324c3e 100644
--- a/benchmark/model_detections/IDEA-Research__grounding-dino-base__richmond.json
+++ b/benchmark/model_detections/IDEA-Research__grounding-dino-base__richmond.json
@@ -1 +1 @@
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\ No newline at end of file
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\ No newline at end of file
diff --git a/benchmark/model_detections/IDEA-Research__grounding-dino-base__sao_paulo.json b/benchmark/model_detections/IDEA-Research__grounding-dino-base__sao_paulo.json
index 9e25a60f..83a8c3b8 100644
--- a/benchmark/model_detections/IDEA-Research__grounding-dino-base__sao_paulo.json
+++ b/benchmark/model_detections/IDEA-Research__grounding-dino-base__sao_paulo.json
@@ -1 +1 @@
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\ No newline at end of file
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\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__annapolis.json b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__annapolis.json
index c66ed7f3..ba847d90 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__annapolis.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__annapolis.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__bend.json b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__bend.json
index 196b9849..0b57f7a7 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__bend.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__bend.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
+{"city":"bend","detections":{"-6wL7HzdK7t8DTC_zDPOLw":[],"0CvMs02xHlg3mCMHJdc6Xg":[[0.8852945121352631,0.6093314264839212,null],[0.06918080571071805,0.6394154180883744,null],[0.11238378798022985,0.6151949477494613,null],[0.044391585351859275,0.6510531719619403,null],[0.15523389616263045,0.7042877808122494,null],[0.06166221611892242,0.5879456539391882,null],[0.3932709961332729,0.6715760719311239,null],[0.19434485457182155,0.7386899043152678,null]],"0FMaNGiSOoTGqLgh8jHfYQ":[[0.1590260906887786,0.5479705127677102,null],[0.2380792771917009,0.5692012165912581,null],[0.30769347121453317,0.6619998209854263,null]],"0SgaioiGd5Yi_5wc6m-nJg":[],"1k8PFgEWlZnrY-j007WMAQ":[],"2S_Fj0bq7qkdKUBw9-g1XA":[[0.8182050701895276,0.6432230272977304,null],[0.11367196137075647,0.6820421703999995,null],[0.26367783587787874,0.7270460275521848,null]],"3EUb8DGIsQCcw8z9LOBnAA":[[0.6009089916472428,0.582145056688289,null]],"4ijauQusmQIJgw4YLTkYsA":[],"5NVgLhChZXnD_D-z3SLZyQ":[[0.6294265400326607,0.6403636256849955,null],[0.7218061692247975,0.6139713907251236,null],[0.26551258423843216,0.5737058115488042,null],[0.3154583214194079,0.5869662074462605,null]],"5U3KS0M2Y8w3qsDGGV610g":[],"62TiKmlmxt_xn_68w1lgAw":[],"6WC0hdAYRsSAcluKSs5iRg":[],"7B5Vphda5PDmZJ5q1RQWdg":[],"87nWq0hrTZLm2_UXRgPhZQ":[[0.9527467093346714,0.5704874212484796,null]],"8H6LgNn56hay95HiBYrhHw":[],"8KtYwvo9b34f3zm-afipNg":[],"8VPbrd8XBzDOIVoo5Xwz8g":[],"8cphEWdm85w5CwOw4rm0_A":[[0.5596727444817047,0.5988093288345031,null],[0.3930570792461361,0.605175151582902,null],[0.32150440216910764,0.611237472143231,null],[0.43459268362601994,0.5634215287537384,null]],"91IlnKR3b8rCc1Zx5XGy7w":[],"9DA1aapwjQcdUP2HEfrhfg":[[0.764953142648753,0.6111368448546993,null],[0.9376187226890569,0.5707526650288968,null],[0.10175033157277952,0.6275251752121486,null],[0.03982052151410098,0.5492392187231614,null]],"9kW9cxpuj7q8DMzf-ClrQQ":[],"A5AVKFhm7unr9Rs55aQ1Tw":[],"BfLStXTTg1-0FjTrZcvYWg":[],"CIdYXefgwcZw4L9PqIpuHQ":[],"DFx_w62mJn4Qm4upFTXytQ":[],"DJ8Zp111zu6KnMZz-0PHgQ":[],"DaCRMtjRrkxBB468GFSAvQ":[[0.6276047581594975,0.5683558951608708,null],[0.6788849953704352,0.5598944731779024,null]],"E15SCY6RTiDuNUu_trZk4Q":[[0.6067329186884445,0.6039658507138995,null],[0.3953224895145856,0.6414409097006637,null],[0.5811191370214719,0.5764338275066176,null],[0.6929771222468785,0.6067645615094376,null],[0.937877328077679,0.5579666150261409,null],[0.8932978387809863,0.5675106782190631,null],[0.10860361645822919,0.5441675413805768,null],[0.27935626972092786,0.5538481649440323,null],[0.08023342791630889,0.5355424597725915,null],[0.41884015924827017,0.6202879976674057,null]],"E1wxX3pnvZdWrWnUkfkNkA":[[0.5670969799835723,0.6293830641120263,null]],"HraXxn_y7_j4o8_4iS_JDQ":[],"I8Y9zDjNKL1k5HUv6BSyFA":[[0.7351538383527263,0.5406943619105224,null],[0.8055240184491522,0.6462748223114829,null],[0.8541160481095046,0.5451651521290819,null]],"IQT-DUkA06hxOus4rPb47A":[],"I_t9Bp1OzV2m-ZKFHssOdg":[[0.08270456654300468,0.5471083554347126,null],[0.932266767879758,0.5669702686111514,null]],"JliGuAWGKCyOS1LBoywZlA":[],"Jv7Zl2erbO_g10pRN-IS_Q":[[0.8208134022343421,0.7163756475352705,null]],"Kv2haiYlkJCiaO61RVWwQA":[[0.7705630216905999,0.6203048103787028,null],[0.9148030835739815,0.5442677118565212,null],[0.06881839182296268,0.5414051264464155,null],[0.1033534407971548,0.5545293102304449,null],[0.9599989662114142,0.5414834683623231,null],[0.25068521470017124,0.5842964018757659,null],[0.29899178172262775,0.6091348032453752,null]],"LMwVmdxU9opG4yzbotuw6g":[],"LN819vhVLLeYwzRsBh2zAg":[[0.7096392622079934,0.6339772456936646,null],[0.2725985372708297,0.6462726638519747,null]],"LhpYKYMPIDXskyHjHW1nOQ":[[0.4780646301888786,0.544578162463644,null],[0.566477728962492,0.5429391135190154,null]],"NS7lT-itv0JiN6UHVvBxsg":[[0.6037776964944854,0.5866579805223792,null],[0.9458597128017159,0.5463563598860273,null],[0.02661318453930339,0.5290227282726231,null]],"Noi7DhIT3xbCjA2Ip4QOyg":[[0.6395457131537607,0.6573990963791898,null],[0.3256860839034642,0.6354333421124161,null]],"NzRL8weHSGkfduBHnrgd5g":[[0.02306348424480159,0.5325210459156802,null]],"OedGesfk606bGhg4OQESiQ":[[0.5666763317602398,0.5634178208401136,null]],"PX5zU_2KkKO0Gr4FiSe9aw":[[0.565191894274239,0.6096233107125348,null],[0.30602875022313647,0.5763158499605283,null]],"PeJlsIXjn8VkEoryRRBBMg":[],"PgOXmiCTtEV4ip7AJDqf2Q":[[0.7461882884237518,0.6728508934345561,null],[0.1826044336684456,0.5569561980145931,null],[0.0786729931926835,0.5311820964710106,null],[0.3852255311568361,0.6571438139543342,null]],"RS0LXKWETF8PhWMbaexYlg":[],"Ro8ZmvW9hyxIS4GVq1cpMQ":[[0.8718938765986617,0.602798803749913,null],[0.12109456246908529,0.6095828126699955,null]],"SM4RUwTVtTzgSm3LWvzwqA":[],"ScnPNQ2cah0xzWlH28uoOw":[[0.6226913475543114,0.6026171777553397,null],[0.6496256401605922,0.5586030557221554,null]],"ShaAxuhgD3rK5__gON66zA":[],"Tn5W3kvbdH7_Fpk29a_hrQ":[[0.560896464025737,0.548733724050593,null],[0.4064182588106002,0.5461267111868054,null]],"TzKDX5ADk6lqRtZ-F8r6XQ":[[0.8038350537362695,0.605807143520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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__budapest_district5.json b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__budapest_district5.json
index e0da2241..3d3dd98b 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__budapest_district5.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__budapest_district5.json
@@ -1 +1 @@
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A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__clovis.json b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__clovis.json
index 0b6f20ab..45089c8b 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__clovis.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__clovis.json
@@ -1 +1 @@
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\ No newline at end of file
+{"city":"clovis","detections":{"1064896187252557":[],"1110562892823067":[],"1115273772298326":[[0.5454218148143664,0.5579647997428042,null],[0.3893541382770131,0.5557908170566881,null],[0.6206627090041198,0.550863197520567,null],[0.31932686065511096,0.5519890568630352,null]],"1181210132352804":[],"1195656127552307":[],"1197447770701938":[],"1198240240634034":[[0.40878607605462,0.6553720329955451,null]],"1207873673000217":[],"1208670676234826":[],"1243806399391315":[[0.34102431010209977,0.5876920426280636,null]],"1281339068951215":[[0.4869210180459709,0.6151878762748997,null]],"1362100907510446":[[0.5352134506042491,0.6683169420731503,null],[0.5744720974385099,0.6358085833411489,null]],"1370371966682122":[],"139019651616598":[],"1414692438885050":[],"142003227963196":[],"144203244404799":[],"148678610517067":[],"150809456962552":[[0.35421569126785807,0.5960438307886076,null]],"1646577775732974":[],"166346065432248":[],"167719748544354":[[0.4694435149633501,0.7040401371033063,null],[0.00957583093824449,0.5855510961042423,null]],"168127948505506":[[0.6411910987472182,0.5876105310576065,null],[0.2900144809656248,0.5468154533131355,null]],"170392751596494":[[0.4346198476037033,0.6248736413215117,null]],"1704575766415957":[[0.4695975969856985,0.5830395776357687,null]],"171723391458583":[],"172282998233890":[[0.3582693105318333,0.6011348473380614,null]],"172922364659417":[],"177108551000367":[],"183964400302616":[[0.8725367200243984,0.5549966322622076,null]],"185678950103109":[[0.05521600713121422,0.5732398631456468,null],[0.04400459045515975,0.6170008775294776,null]],"1878739745614992":[],"192621366051825":[],"195183319043473":[],"1978660535622283":[],"203883874892763":[],"204886314666549":[],"217080690010555":[],"219131249781847":[[0.4525097988863939,0.7779881134191156,null]],"221917589460448":[],"222124426103957":[[0.0863147466999426,0.6174076731872863,null],[0.34246557203359684,0.6747074176876805,null]],"232786268184386":[],"232891661506981":[],"233474051445151":[],"2493443314123605":[],"259170445960040":[],"2652019851757090":[],"285195270004030":[[0.6148237062392914,0.6288640746443406,null]],"2904429339832545":[],"2908033546190932":[],"2909136316010153":[[0.3366020853203078,0.5428042504696748,null]],"2938602763134225":[[0.96455486320835,0.5698515332591216,null],[0.8802380984278504,0.5526524744061553,null],[0.39820623781360265,0.6847670675800462,null]],"2977612369225705":[],"2979119369077618":[],"298740268622763":[],"301397241499290":[],"301640868358262":[],"3043158182635438":[[0.6020998951484842,0.63408510851917,null]],"308441850838672":[[0.680675363337129,0.5584278537710364,null],[0.3299509220712903,0.5629014190537004,null]],"308559267339828":[[0.062463904610475185,0.5524445093543309,null]],"310589334058179":[],"311175153796836":[],"314281570321010":[[0.2997319703648977,0.607417075256102,null]],"323628349333170":[],"3264932050400483":[],"327979002173875":[],"331704768384211":[],"341385827421059":[],"3706361862807633":[],"373977847581697":[[0.6783236838100396,0.578089804192597,null]],"376064363845819":[],"3893017870814523":[],"3906688372733138":[],"3912015842228191":[],"3939249736143912":[[0.6188511787609212,0.552568071141227,null],[0.6711846514413384,0.5507752103691694,null],[0.9066378266561871,0.5488465532686921,null]],"3975206075849203":[[0.9409373135376545,0.6216044880905575,null],[0.9173586304289731,0.6154471984394181,null]],"3975990335818804":[[0.603578520301496,0.6656533381531389,null],[0.8618063585038918,0.6249495024636144,null]],"4029786067103641":[],"4088414157885402":[],"4134475506643495":[],"4142410022468972":[],"4347306715281715":[],"4648083425204950":[[0.6744385466035396,0.5465920428253491,null]],"476824956956024":[],"477834906826400":[[0.5649426253895439,0.5502654385650138,null]],"483031622925446":[[0.6611332091161609,0.5628782193544203,null],[0.41899394865903133,0.5843417668858748,null]],"483328876252454":[],"490105898988611":[[0.5425455206635684,0.7121721190438242,null]],"490344308689064":[[0.5436504194203664,0.5893151810493571,null]],"492435855406236":[],"494271831919687":[[0.42940215630619194,0.6773981992110905,null]],"499704301465714":[],"504758370672604":[],"506669223705998":[],"507337747134100":[],"507362710300684":[],"517195446066836":[[0.6754721766306475,0.598202943555502,null]],"525644228599460":[],"531478437866297":[],"542282330125531":[],"545146053319322":[],"637757707623691":[],"744451279581577":[],"755820925099849":[],"773395216705340":[[0.6378848519605639,0.6517966856198236,null],[0.43719516604885766,0.7027191813086856,null]],"775225080310516":[[0.6156254152046804,0.5944918631139771,null]],"777059616337842":[],"777844299592863":[],"778142686176383":[],"796298687952468":[],"805303977081180":[[0.6819502326517085,0.5550166351270749,null],[0.30406197180694394,0.5604770219168184,null]],"807482166820261":[[0.37878700712898283,0.6383768005463518,null]],"812831093002742":[],"825040278408836":[],"841498166782932":[],"856069755259257":[],"858708244726347":[],"870854823644900":[],"87494789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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__gainesville.json b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__gainesville.json
index f2048dd9..630bf5c2 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__gainesville.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__gainesville.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
+{"city":"gainesville","detections":{"--xM_B9BVXSNT9IcytVKug":[],"-FMeOe5iGG-5JFxSF0lxaQ":[[0.40072328429975956,0.567908172025597,null],[0.5905778438264666,0.6086957991700394,null]],"-Thw-Y56uiaGEg8I_zZwgw":[],"-zi5tN6Qyyeq8B1mczYfOg":[],"08ssXvyy311t_dOt8e3MVA":[[0.8522680564186984,0.5854180047791644,null]],"1n-U7MQVuboJf00fwh9UBg":[],"21qHYEKoNSGw9O3wF_dvBg":[],"2ZG41STPUADAWUJD-Rc4sA":[],"2xfTrO6eZbF0hKmvjGzN0A":[],"3CbLaqDP3N3z64brBrC0eA":[[0.07417963052201632,0.542968034839125,null]],"4ILOJcaHD7m47NGoY6aqRg":[],"4My9h4mmpjE82U1up3jWOA":[[0.6329287005861911,0.5635047142863365,null]],"5vEoUj3H3aRkW-2h1B0JAQ":[[0.6284503534697989,0.6613212283759781,null]],"6-tNVth5ck0axWmPuKpiXg":[],"65kxFTBgmbOPUQbC612rdg":[[0.6878732257865341,0.6189301122941102,null],[0.9194162375697426,0.6018511626701442,null],[0.27924784592315954,0.6337967719856221,null],[0.3112042575171068,0.6080803976217608,null]],"6HfrzDBSveHUN1NpGsF31Q":[],"6KnaArlg4nGEGAGNkIw9NA":[],"6esDvYaAUiUdZHtq1FCAfg":[[0.7499497802796474,0.7467459019944875,null],[0.6836360372125807,0.6112453010996245,null],[0.7294281395262183,0.7301303376295128,null],[0.11117594816814991,0.6785701155359477,null]],"6mZXrVGoxQ2H1k8Jx2OZHA":[],"7U40JKd7HiOpFrTHa0-yQQ":[],"7Vk-zugISgNBVOV4g3r2jA":[[0.9473611628956145,0.6036502837164716,null]],"7dme7qsPcOTglSlmpGp9Rw":[],"82y6sIvPm-_shG58klusgw":[],"89lilp2BlhppxL-oQ0gLNg":[],"8FPxXspDHn_FNxmQkr0j-g":[],"9D-oOS00uSg18nvfm8t9zQ":[[0.39149773683189215,0.5805275137367915,null],[0.7150853325403919,0.6209031478706389,null],[0.8828934082420246,0.6027034912658562,null],[0.3648366076137707,0.659866449909988,null]],"9QF3VpTsXpZei70YvA-H6w":[],"9tS6faHm3jFdOth84XlbEQ":[[0.946669616405349,0.5595486483728207,null],[0.8400485325167855,0.5723727009891897,null],[0.07805767819954623,0.5582091651120328,null],[0.09785862811767837,0.5836549962884181,null],[0.260570574901149,0.5575717421878963,null]],"A44roYJy6tdzAK9yLNS_qQ":[],"AVRG2QwkPWmeX2iPSnKDcw":[],"BtYzecFoq3-H5qaGzBh4iw":[],"BzXolOMX-XSEGwyXQpIsrA":[[0.6070894533952813,0.6427570492324541,null]],"CaClPAIWuWDFsoftxxmRig":[],"CabndIEXzzs5FAENnrsEug":[],"D5NlzcW2s95DlOUPY0cVAw":[],"DSID5BsZ19qz5BuvC_ZDNA":[[0.778287633915052,0.7288418075935443,null]],"DXKg24FIKMrGUX6ilHn5Ew":[],"E2YAOGNgsJYuHjnUBvnjFg":[],"EhBhDcmWUDV5CaBKoAqi0A":[],"FZOcjvm34N_9JGZyXQf7dg":[],"G7ttNgjW4KU9LJVeD1Ivdg":[],"GJ9IMVsb4ULLwoTYEUCZtA":[],"GRTC3zOCFSc8QMIrAtwtzw":[[0.3882044307796574,0.5878245976855059,null],[0.6105199001723457,0.6671333923682324,null],[0.34072687566685983,0.5521321411073041,null],[0.2229703070072886,0.5698815430210206,null],[0.2989395792156222,0.5620478326050025,null]],"GhbzPi4bva0g3AlMDcioOg":[],"HLLOIKVLXvOkBCREUvcBzg":[],"HoOapW5g53qbEFjLA7yv3Q":[],"ICUoYVV_dXvc9W3ge2PnWg":[],"Idfm_UDnRFcD78ZVeNnhVg":[[0.5306245347500875,0.5250437840343496,null],[0.6213938831002702,0.5793865359680082,null]],"JOK56E_pGy9cwNPyiymZ2A":[],"JlYp0BtvGCVeIqBady7pGg":[],"K732QTWoB9RZwrfSmw7RYA":[[0.32482283282662927,0.6003399212086846,null]],"KEwb17BzIjKVur60MpItuA":[[0.6027678967390302,0.6195791287216071,null]],"KH6m80K7GCy3eVrCdRMYZA":[],"KbZFzQai9wfXijoQDscWFw":[[0.7072483291991742,0.6759544403838946,null]],"KqZzM0v2PbaoxQmq6wk3Xw":[[0.11509440020607142,0.5543171113358192,null]],"LDICnJgAhCSszYwolm8JRA":[],"LEM6UenW5sPkdj5aaW4thw":[],"LLc383eAyneHduBTInH9nw":[],"MTDJakccuk6hQfnZ3QEjxQ":[],"MVFGRGfew07C0mMkeXxhCA":[],"Mg3-OQnBkIqnfi4qnO5KbQ":[],"Mm5gyUYqmJmjeGopC1IgKg":[[0.394782266413765,0.5865895701152725,null],[0.5400525604916958,0.569944933398841,null]],"PSS2iz32Sj0nE2ILJ6i8rA":[[0.6181123363442586,0.5669699103124223,null]],"P_bUUx5CIFcylFd9UAZRug":[[0.7189185692326542,0.5402934912431365,null]],"SxMVl_DRQndQkQAvu9a01Q":[],"TsU9TS4hpMHXVwv-YIrvCQ":[[0.6081694431868623,0.6220983133154554,null]],"UPTPPrW6iUFocod220aq8g":[[0.7103851032090063,0.6748826019741014,null]],"UrwK5NxGtb1p1lGv2EIgdg":[[0.6266264574898779,0.5632078651139137,null],[0.30359890748876905,0.5491067129820927,null]],"V1ze8IkgvM7tXueCGVfzbw":[[0.7873616601315576,0.6180820737584889,null],[0.1869478760900114,0.5832628428648854,null]],"VWMApFeYDoQmO9taDRV-lg":[[0.40024465160330813,0.6409225489163021,null],[0.897506011526666,0.6333106964450522,null]],"VYsAOBkJ-7hdoDBIOhr-nQ":[],"Vk6u3cbrlksc6Cy5a1LVVA":[[0.02568474603201143,0.5501462397612339,null]],"WVSHD61mDgZmv8fnzj3i6Q":[],"X45JWReulQB2gYvNrbUKGA":[],"XRcpuzY4BC5AypmNXaQuyQ":[],"XWhHaUuheK2ypAkTt10B8A":[[0.9168089173179212,0.6384404493451032,null],[0.4202663291696085,0.5359420204694676,null]],"XuX3LCIaNmEI9FSBenjToA":[],"YDTr8LXPDt5ieA8MA6ZXLA":[],"YckCrqJ_I8sBF8wU5FpITw":[],"Z0pMjC8iJ6EDQzsBBrr_5Q":[],"_2GSllZzac7Zfd02VoVgCA":[],"amZHKZbJ7pOJ9kvr2VlK5A":[[0.8356313556407279,0.7729656602941952,null],[0.8579332187669624,0.7639350069550976,null],[0.29215181475219665,0.5735034953474827,null],[0.36361281479842644,0.5598465625795693,null]],"b-azHLq5uJSlywVqKYbgHA":[[0.16155845415838127,0.6040899430979969,null]],"bcNsOc7RlDm9L9VmIGXYpg":[[0.4085643379493906,0.5875451157375658,null]],"dVrNCxUTFAfeyVNMXQ1LTw":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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__manual_gold.json b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__manual_gold.json
index 191a1226..2854da85 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__manual_gold.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__manual_gold.json
@@ -1 +1 @@
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wen3-VL-32B-Instruct","prompt":"Detect every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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048,"max_new_tokens":1024,"model_id":"Qwen/Qwen3-VL-32B-Instruct","prompt":"Detect every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__morgantown.json b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__morgantown.json
index aba6c115..bd792542 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__morgantown.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__morgantown.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__paterson.json b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__paterson.json
index 8a447d3c..574e0278 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__paterson.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__paterson.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__richmond.json b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__richmond.json
index e7b02889..4f645049 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__richmond.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__richmond.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__sao_paulo.json b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__sao_paulo.json
index cc08943f..f24ee043 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__sao_paulo.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-32B-Instruct__sao_paulo.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__annapolis.json b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__annapolis.json
index b0c37731..b575d495 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__annapolis.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__annapolis.json
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__bend.json b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__bend.json
index 9fcf7246..c114afe2 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__bend.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__bend.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__budapest_district5.json b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__budapest_district5.json
index aa4b85b6..2ead0483 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__budapest_district5.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__budapest_district5.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__clovis.json b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__clovis.json
index 59d2a8ba..616562e8 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__clovis.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__clovis.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__gainesville.json b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__gainesville.json
index 84a4525d..0134cdfa 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__gainesville.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__gainesville.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__manual_gold.json b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__manual_gold.json
index 6905150e..c5201203 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__manual_gold.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__manual_gold.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__morgantown.json b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__morgantown.json
index d1e5c155..3a5e76b3 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__morgantown.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__morgantown.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__paterson.json b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__paterson.json
index c520b406..a7908b2e 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__paterson.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__paterson.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__richmond.json b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__richmond.json
index 492c29c2..7e69cb4e 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__richmond.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__richmond.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__sao_paulo.json b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__sao_paulo.json
index 2a45c1da..293d97cc 100644
--- a/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__sao_paulo.json
+++ b/benchmark/model_detections/Qwen__Qwen3-VL-8B-Instruct__sao_paulo.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list. Respond with JSON only: a list of {\"bbox_2d\": [x1, y1, x2, y2], \"label\": \"curb ramp\"}.","provider":"qwen","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/allenai__Molmo2-8B__annapolis.json b/benchmark/model_detections/allenai__Molmo2-8B__annapolis.json
index e9b9d9bd..c4f1daf1 100644
--- a/benchmark/model_detections/allenai__Molmo2-8B__annapolis.json
+++ b/benchmark/model_detections/allenai__Molmo2-8B__annapolis.json
@@ -1 +1 @@
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/allenai__Molmo2-8B__bend.json b/benchmark/model_detections/allenai__Molmo2-8B__bend.json
index 1b7b6edb..86120a9d 100644
--- a/benchmark/model_detections/allenai__Molmo2-8B__bend.json
+++ b/benchmark/model_detections/allenai__Molmo2-8B__bend.json
@@ -1 +1 @@
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/allenai__Molmo2-8B__budapest_district5.json b/benchmark/model_detections/allenai__Molmo2-8B__budapest_district5.json
index b5f2fc50..ef66d0c4 100644
--- a/benchmark/model_detections/allenai__Molmo2-8B__budapest_district5.json
+++ b/benchmark/model_detections/allenai__Molmo2-8B__budapest_district5.json
@@ -1 +1 @@
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/allenai__Molmo2-8B__clovis.json b/benchmark/model_detections/allenai__Molmo2-8B__clovis.json
index 10f2ed7c..08078d3e 100644
--- a/benchmark/model_detections/allenai__Molmo2-8B__clovis.json
+++ b/benchmark/model_detections/allenai__Molmo2-8B__clovis.json
@@ -1 +1 @@
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/allenai__Molmo2-8B__gainesville.json b/benchmark/model_detections/allenai__Molmo2-8B__gainesville.json
index 0ae211d9..2a5c9429 100644
--- a/benchmark/model_detections/allenai__Molmo2-8B__gainesville.json
+++ b/benchmark/model_detections/allenai__Molmo2-8B__gainesville.json
@@ -1 +1 @@
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/allenai__Molmo2-8B__manual_gold.json b/benchmark/model_detections/allenai__Molmo2-8B__manual_gold.json
index f7a6d759..281b9019 100644
--- a/benchmark/model_detections/allenai__Molmo2-8B__manual_gold.json
+++ b/benchmark/model_detections/allenai__Molmo2-8B__manual_gold.json
@@ -1 +1 @@
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/allenai__Molmo2-8B__morgantown.json b/benchmark/model_detections/allenai__Molmo2-8B__morgantown.json
index 44aef62f..19e9c716 100644
--- a/benchmark/model_detections/allenai__Molmo2-8B__morgantown.json
+++ b/benchmark/model_detections/allenai__Molmo2-8B__morgantown.json
@@ -1 +1 @@
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/allenai__Molmo2-8B__paterson.json b/benchmark/model_detections/allenai__Molmo2-8B__paterson.json
index d340cd19..1b27d982 100644
--- a/benchmark/model_detections/allenai__Molmo2-8B__paterson.json
+++ b/benchmark/model_detections/allenai__Molmo2-8B__paterson.json
@@ -1 +1 @@
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/allenai__Molmo2-8B__richmond.json b/benchmark/model_detections/allenai__Molmo2-8B__richmond.json
index c2e20ce7..c01ce7c6 100644
--- a/benchmark/model_detections/allenai__Molmo2-8B__richmond.json
+++ b/benchmark/model_detections/allenai__Molmo2-8B__richmond.json
@@ -1 +1 @@
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/allenai__Molmo2-8B__sao_paulo.json b/benchmark/model_detections/allenai__Molmo2-8B__sao_paulo.json
index ff976ddc..40a4995b 100644
--- a/benchmark/model_detections/allenai__Molmo2-8B__sao_paulo.json
+++ b/benchmark/model_detections/allenai__Molmo2-8B__sao_paulo.json
@@ -1 +1 @@
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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to every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Put one point at the center of each curb ramp. Do not point at driveways, stairs, or crosswalk paint. If there are no curb ramps, say so.","provider":"molmo","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.1-pro-preview__annapolis.json b/benchmark/model_detections/gemini-3.1-pro-preview__annapolis.json
index 00180b8e..16a0befb 100644
--- a/benchmark/model_detections/gemini-3.1-pro-preview__annapolis.json
+++ b/benchmark/model_detections/gemini-3.1-pro-preview__annapolis.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.1-pro-preview__bend.json b/benchmark/model_detections/gemini-3.1-pro-preview__bend.json
index 57ba43b9..52c95a3a 100644
--- a/benchmark/model_detections/gemini-3.1-pro-preview__bend.json
+++ b/benchmark/model_detections/gemini-3.1-pro-preview__bend.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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3945552678674,0.7235841631021314,null],[0.8148985666894822,0.7521272778646017,null],[0.841066327924856,0.7548643690728603,null],[0.15285499827865273,0.6108266197671806,null],[0.3758863401983247,0.5498259551340497,null]],"yPUv9rk8acshJKXa9_jMag":[[0.5310776448516401,0.5581159864455836,null],[0.04134809649027854,0.5309988472156602,null]],"yuwkp3XCUwSbB8q7Og99GQ":[[0.8852403370290475,0.5862389190457418,null],[0.111008985670767,0.5672841884453432,null]],"zR6d6XkSFO-UYbgkD26kkw":[],"zcVgeJb6FkDw1z__YhM1tg":[[0.637270421466139,0.6168106437611045,null],[0.8650432444468525,0.5589061635399699,null],[0.025115486571456958,0.5239168704740248,null],[0.2124754657382139,0.8051956136642039,null]]},"model":"gemini-3.1-pro-preview","n_panos":110,"n_uncached":0,"published_as":"gemini-3.1-pro-preview","signature":{"max_edge":1568,"model_id":"gemini-3.1-pro-preview","prompt":"Detect every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.1-pro-preview__budapest_district5.json b/benchmark/model_detections/gemini-3.1-pro-preview__budapest_district5.json
index 695a04f1..0acc6ceb 100644
--- a/benchmark/model_detections/gemini-3.1-pro-preview__budapest_district5.json
+++ b/benchmark/model_detections/gemini-3.1-pro-preview__budapest_district5.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.1-pro-preview__clovis.json b/benchmark/model_detections/gemini-3.1-pro-preview__clovis.json
index e09229e2..9bb8781a 100644
--- a/benchmark/model_detections/gemini-3.1-pro-preview__clovis.json
+++ b/benchmark/model_detections/gemini-3.1-pro-preview__clovis.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.1-pro-preview__gainesville.json b/benchmark/model_detections/gemini-3.1-pro-preview__gainesville.json
index 267abcbc..2fce3823 100644
--- a/benchmark/model_detections/gemini-3.1-pro-preview__gainesville.json
+++ b/benchmark/model_detections/gemini-3.1-pro-preview__gainesville.json
@@ -1 +1 @@
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,"xMY6EkmbN9OZqwHeC_S7Zg":[[0.4137855227336352,0.5900728141666791,null],[0.8352156719626735,0.6261354265017002,null],[0.9725825171167823,0.5688192904099916,null]],"yQOkeKGLo1dFuhOO7BFRFg":[[0.6390476918645173,0.5634048941045351,null],[0.8255602532133195,0.5939966980812076,null]],"zTwcPkPUYZ7lRIowR3wXyg":[]},"model":"gemini-3.1-pro-preview","n_panos":125,"n_uncached":0,"signature":{"max_edge":1568,"model_id":"gemini-3.1-pro-preview","prompt":"Detect every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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,"xMY6EkmbN9OZqwHeC_S7Zg":[[0.4137855227336352,0.5900728141666791,null],[0.8352156719626735,0.6261354265017002,null],[0.9725825171167823,0.5688192904099916,null]],"yQOkeKGLo1dFuhOO7BFRFg":[[0.6390476918645173,0.5634048941045351,null],[0.8255602532133195,0.5939966980812076,null]],"zTwcPkPUYZ7lRIowR3wXyg":[]},"model":"gemini-3.1-pro-preview","n_panos":125,"n_uncached":0,"published_as":"gemini-3.1-pro-preview","signature":{"max_edge":1568,"model_id":"gemini-3.1-pro-preview","prompt":"Detect every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.1-pro-preview__morgantown.json b/benchmark/model_detections/gemini-3.1-pro-preview__morgantown.json
index d9a3c102..b50738f7 100644
--- a/benchmark/model_detections/gemini-3.1-pro-preview__morgantown.json
+++ b/benchmark/model_detections/gemini-3.1-pro-preview__morgantown.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.1-pro-preview__paterson.json b/benchmark/model_detections/gemini-3.1-pro-preview__paterson.json
index c957bb72..33f6a679 100644
--- a/benchmark/model_detections/gemini-3.1-pro-preview__paterson.json
+++ b/benchmark/model_detections/gemini-3.1-pro-preview__paterson.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.1-pro-preview__richmond.json b/benchmark/model_detections/gemini-3.1-pro-preview__richmond.json
index 2471020e..299f276d 100644
--- a/benchmark/model_detections/gemini-3.1-pro-preview__richmond.json
+++ b/benchmark/model_detections/gemini-3.1-pro-preview__richmond.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.1-pro-preview__sao_paulo.json b/benchmark/model_detections/gemini-3.1-pro-preview__sao_paulo.json
index 42d3a2ea..86a1506e 100644
--- a/benchmark/model_detections/gemini-3.1-pro-preview__sao_paulo.json
+++ b/benchmark/model_detections/gemini-3.1-pro-preview__sao_paulo.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.6-flash__annapolis.json b/benchmark/model_detections/gemini-3.6-flash__annapolis.json
index 6476e83f..7eacaa2c 100644
--- a/benchmark/model_detections/gemini-3.6-flash__annapolis.json
+++ b/benchmark/model_detections/gemini-3.6-flash__annapolis.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.6-flash__bend.json b/benchmark/model_detections/gemini-3.6-flash__bend.json
index ff6cfff9..f1fd9853 100644
--- a/benchmark/model_detections/gemini-3.6-flash__bend.json
+++ b/benchmark/model_detections/gemini-3.6-flash__bend.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.6-flash__budapest_district5.json b/benchmark/model_detections/gemini-3.6-flash__budapest_district5.json
index c13f3911..8a5e332d 100644
--- a/benchmark/model_detections/gemini-3.6-flash__budapest_district5.json
+++ b/benchmark/model_detections/gemini-3.6-flash__budapest_district5.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.6-flash__clovis.json b/benchmark/model_detections/gemini-3.6-flash__clovis.json
index c926589f..2276cfcd 100644
--- a/benchmark/model_detections/gemini-3.6-flash__clovis.json
+++ b/benchmark/model_detections/gemini-3.6-flash__clovis.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.6-flash__gainesville.json b/benchmark/model_detections/gemini-3.6-flash__gainesville.json
index f2c116ca..ce1011e0 100644
--- a/benchmark/model_detections/gemini-3.6-flash__gainesville.json
+++ b/benchmark/model_detections/gemini-3.6-flash__gainesville.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.6-flash__morgantown.json b/benchmark/model_detections/gemini-3.6-flash__morgantown.json
index 890a92f5..e14be0cf 100644
--- a/benchmark/model_detections/gemini-3.6-flash__morgantown.json
+++ b/benchmark/model_detections/gemini-3.6-flash__morgantown.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.6-flash__paterson.json b/benchmark/model_detections/gemini-3.6-flash__paterson.json
index 5ad4d1e6..36642ede 100644
--- a/benchmark/model_detections/gemini-3.6-flash__paterson.json
+++ b/benchmark/model_detections/gemini-3.6-flash__paterson.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.6-flash__richmond.json b/benchmark/model_detections/gemini-3.6-flash__richmond.json
index 6ca3ab67..1a127dff 100644
--- a/benchmark/model_detections/gemini-3.6-flash__richmond.json
+++ b/benchmark/model_detections/gemini-3.6-flash__richmond.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.6-flash__sao_paulo.json b/benchmark/model_detections/gemini-3.6-flash__sao_paulo.json
index b57f514b..7cdb359e 100644
--- a/benchmark/model_detections/gemini-3.6-flash__sao_paulo.json
+++ b/benchmark/model_detections/gemini-3.6-flash__sao_paulo.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.7-flash__annapolis.json b/benchmark/model_detections/gemini-3.7-flash__annapolis.json
index 5c1d4d4c..752a77df 100644
--- a/benchmark/model_detections/gemini-3.7-flash__annapolis.json
+++ b/benchmark/model_detections/gemini-3.7-flash__annapolis.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.7-flash__bend.json b/benchmark/model_detections/gemini-3.7-flash__bend.json
index 05bea067..3803fa79 100644
--- a/benchmark/model_detections/gemini-3.7-flash__bend.json
+++ b/benchmark/model_detections/gemini-3.7-flash__bend.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.7-flash__budapest_district5.json b/benchmark/model_detections/gemini-3.7-flash__budapest_district5.json
index 8dfc96f3..56c83a61 100644
--- a/benchmark/model_detections/gemini-3.7-flash__budapest_district5.json
+++ b/benchmark/model_detections/gemini-3.7-flash__budapest_district5.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.7-flash__clovis.json b/benchmark/model_detections/gemini-3.7-flash__clovis.json
index 5e7b1db3..0ca8f518 100644
--- a/benchmark/model_detections/gemini-3.7-flash__clovis.json
+++ b/benchmark/model_detections/gemini-3.7-flash__clovis.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.7-flash__gainesville.json b/benchmark/model_detections/gemini-3.7-flash__gainesville.json
index 013a3f15..9e2dced7 100644
--- a/benchmark/model_detections/gemini-3.7-flash__gainesville.json
+++ b/benchmark/model_detections/gemini-3.7-flash__gainesville.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.7-flash__manual_gold.json b/benchmark/model_detections/gemini-3.7-flash__manual_gold.json
index e96f0ed9..5b20dfdd 100644
--- a/benchmark/model_detections/gemini-3.7-flash__manual_gold.json
+++ b/benchmark/model_detections/gemini-3.7-flash__manual_gold.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.7-flash__morgantown.json b/benchmark/model_detections/gemini-3.7-flash__morgantown.json
index 2d6bcc59..21a5f6cd 100644
--- a/benchmark/model_detections/gemini-3.7-flash__morgantown.json
+++ b/benchmark/model_detections/gemini-3.7-flash__morgantown.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.7-flash__paterson.json b/benchmark/model_detections/gemini-3.7-flash__paterson.json
index 200b391d..8e1bc084 100644
--- a/benchmark/model_detections/gemini-3.7-flash__paterson.json
+++ b/benchmark/model_detections/gemini-3.7-flash__paterson.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.7-flash__richmond.json b/benchmark/model_detections/gemini-3.7-flash__richmond.json
index 281a602a..a13c0408 100644
--- a/benchmark/model_detections/gemini-3.7-flash__richmond.json
+++ b/benchmark/model_detections/gemini-3.7-flash__richmond.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/gemini-3.7-flash__sao_paulo.json b/benchmark/model_detections/gemini-3.7-flash__sao_paulo.json
index 15cacc17..02b219c9 100644
--- a/benchmark/model_detections/gemini-3.7-flash__sao_paulo.json
+++ b/benchmark/model_detections/gemini-3.7-flash__sao_paulo.json
@@ -1 +1 @@
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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
+{"city":"sao_paulo","detections":{"--g3UwVswwny7hOlxl77-w":[],"-pcHlrGDC4hPPRHVxU3W3Q":[[0.7259515952015987,0.6576656576478046,null],[0.7774969032226358,0.6160663935206256,null],[0.6975606390533362,0.6684212878405884,null]],"-uqS0QNM8aUFtP5gwTMu4w":[[0.18285914772834572,0.6252447867750262,null],[0.27375959265153427,0.63720520906194,null],[0.30490758658301265,0.6308566367783135,null]],"0aJabNkZdyIHXbiruS_yLw":[[0.08302146731831939,0.5626758556284394,null]],"0rG2QcmPAKBBec7NcS_SUw":[],"1bF6KihYF1Rw8PIg_ZTh6g":[[0.3736575274103664,0.6006993310923173,null]],"23nSVF67ExPhVWfty9-4Qw":[],"2L64Zqq-r58lo_7JVUoJSA":[[0.40604036708891955,0.5851087463635817,null],[0.618760307414164,0.5607027822135077,null],[0.8261706853235313,0.5970372273172964,null],[0.16121220625523924,0.6059212972355216,null]],"2XdWe9r6z5m-9SmNQq7TGQ":[],"2vVoZEbjn1wxGCCvCmgeUQ":[[0.6190257279960076,0.6214188139294804,null],[0.9386175967049801,0.5716390077966718,null],[0.3009942510966587,0.6366952677554213,null],[0.3253357069101114,0.6231874263102362,null]],"31AcIQn0F7vJCIRP7U4gyA":[[0.874183805722488,0.6087485576475701,null],[0.12922206619982596,0.6133609516184264,null],[0.15893447827315044,0.6288290089655695,null]],"3SnxAqXSf1WzcWlp76h_2Q":[[0.7777117573334689,0.5720241607856447,null],[0.800682046089843,0.5735443735275738,null],[0.23628775894640897,0.6164896900156498,null],[0.29732973772304216,0.6101105679245491,null]],"3lHC4L5HK6yvXRZfPYnUqg":[[0.5980349652673321,0.5609601255816339,null],[0.07585746746834882,0.545711520472457,null]],"4RXNxzYjFwN0EBvKh8aHSQ":[[0.6253133978388848,0.615761635891242,null],[0.9054424021528849,0.545470366423264,null],[0.330774343747655,0.5862847821572437,null]],"4Z4bj21zN62_fBZJzoF6Xg":[],"4n8b3OMdbJZgeJXz_TxNBA":[[0.7443002437932311,0.6641647712416417,null],[0.8684680848819548,0.6437384509518607,null],[0.22664614885036555,0.6063067276260086,null]],"52VthEdI90oCcFRLa9Wy5g":[[0.1218501140450523,0.5942352083613094,null]],"53l0gQcJPK4NrZhJZhtKlg":[],"5IK4jyU16o627F2yDHu6Gw":[[0.05987457739352192,0.5530477410432478,null]],"5b-MNFZDk9yhziWPr2u7Hg":[],"6a_UTgidEGA0mlGKPlurNw":[[0.37680933410043876,0.671110302155175,null],[0.7929337153158249,0.6326388409208257,null],[0.2865833514194661,0.6493421873625169,null]],"6fpdvTPOA_R4Jb9bCBCwug":[],"74L65cpBc6Sv_D15h1n4Rw":[],"7O-o_5mVjT3KdC0SV0shUw":[[0.6086390478466726,0.5874454375939524,null],[0.7778747560558621,0.5639301841862876,null],[0.95556287736425,0.5764423565746699,null]],"7RmzjvAikTNecf6xoiPw4Q":[],"7UTz_5Xfnx4Hz_0gfN2WZA":[[0.1642645870724354,0.7115488882336866,null]],"7um0A6G_bSJ3Hn6nRbixvA":[[0.7789704240737754,0.7142730919960165,null],[0.2251890770994442,0.5841636992568093,null],[0.2692518110143427,0.582796759767648,null]],"8PunOGXWhLW2Jcp-z1kSNg":[],"8qkdHYilRAI7Vrdpg2XuDw":[],"9MaI1wktdWe6O8uAN_-zYg":[],"9e52qBoSx6RlPRP2VHBTqA":[[0.6936614209445786,0.5628817139230926,null],[0.44563443375198414,0.5564474941816439,null]],"9ogLSXwqkmRsXUlTLya0uQ":[[0.7135324787658472,0.6233603930712824,null],[0.7878263556635356,0.6462330207386209,null],[0.8159373868438402,0.6487270795477253,null],[0.1302819998833778,0.6123804941444613,null],[0.22606288849059297,0.6079156462201909,null],[0.38712871845892055,0.5440420095033971,null]],"AJMyOxILJ9hobRi9AdqnCw":[],"AJVnpStT1x3aP5rNLkUUyA":[[0.5275154967691291,0.5331617510342538,null],[0.36131075911840693,0.5710688843315087,null]],"AyVE6TqZxahbZyzOG8KhPg":[],"BK29yXSNmXidi-3ggxm_Zg":[[0.9175848742833372,0.5980798788093534,null],[0.2400584127257444,0.5970028242380679,null]],"Cuj3qJDAZnTKnMhQLXy1ig":[[0.9008693918392892,0.6666239195523037,null]],"DSdxd4wO-H8l4g-O_IGfkg":[[0.5757494784070435,0.5738762252114142,null]],"E2-oeApmq0sW_GDdLFbnCQ":[[0.7774135788355094,0.6757622818910582,null],[0.29412064347614386,0.59258897573454,null]],"FRKJomHWa7nYfbmGJRNuvA":[],"GnxqQAq5GVonmVKfcMcr6w":[],"H2cEJygbNd56-362PsICjA":[[0.5990547324544108,0.5833248152984851,null],[0.36378009875353157,0.574894910764534,null]],"I0LGgFwBsGIYNbIsIaLgpQ":[[0.724657216765898,0.6088459090173898,null]],"IAF46f7Lfz65Y2vjckHeMA":[[0.8180330934891126,0.58561886630869,null],[0.2235406815136735,0.617721663578889,null],[0.2810186298241956,0.5977547020547616,null]],"JAwR7rGXLysrpeYgTzkLCQ":[[0.8889272089462241,0.6471507436131541,null],[0.14346481950668333,0.7172153635060776,null]],"JF3A8_EnhGARQxmfqdpANA":[[0.718585203906038,0.5762827507063447,null],[0.28644805335350926,0.6185960685655681,null]],"KD-uKFrh3oLPfzbwOStEWA":[],"LUW-LxIfrK_j7kCq16WoyQ":[[0.772004039178694,0.6280393626326757,null],[0.7076279712060617,0.6366446751426265,null],[0.9229199314584762,0.5563468271743512,null]],"LfPVRvshATNPaK78qOt-Ug":[],"M5mjc-BAtPFJppa9npq4xA":[[0.615957577651315,0.6180975443641932,null],[0.26250799540364056,0.5782739221325864,null]],"MBuniYPiSz9apm9agSpqPw":[[0.6269329636168695,0.5785397880367267,null]],"MO1IiuyyjHfY4uBuEsgoeg":[[0.7170683535074365,0.6442731519955015,null]],"MTKGGsTjIZqzb5CJ4L_zKw":[],"MjzhJxGXvpsFuKgE1Mh-Xg":[],"N2dp00E-bFRP97GdlN6YgA":[[0.27530391192737136,0.6025201956630084,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every curb ramp in this street-level image. A curb ramp (curb cut) is the short sloped ramp cut into a sidewalk curb at a street corner or crossing that lets a wheelchair or stroller roll from sidewalk to street. Return one tight bounding box per curb ramp. Do not box driveways, stairs, or crosswalk paint. If there are no curb ramps, return an empty list.","provider":"gemini","source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__annapolis.json b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__annapolis.json
index ae6e5b2d..b501f95f 100644
--- a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__annapolis.json
+++ b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__annapolis.json
@@ -1 +1 @@
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\ No newline at end of file
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photo of a curb ramp","provider":"owlv2","query":"a photo of a curb ramp","score_threshold":0.05,"source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__bend.json b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__bend.json
index 002c55bd..c71148b8 100644
--- a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__bend.json
+++ b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__bend.json
@@ -1 +1 @@
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\ No newline at end of file
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photo of a curb ramp","provider":"owlv2","query":"a photo of a curb ramp","score_threshold":0.05,"source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__budapest_district5.json b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__budapest_district5.json
index 9f71e1b0..1a083745 100644
--- a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__budapest_district5.json
+++ b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__budapest_district5.json
@@ -1 +1 @@
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\ No newline at end of file
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photo of a curb ramp","provider":"owlv2","query":"a photo of a curb ramp","score_threshold":0.05,"source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__clovis.json b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__clovis.json
index f970b225..ec7d2db5 100644
--- a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__clovis.json
+++ b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__clovis.json
@@ -1 +1 @@
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\ No newline at end of file
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photo of a curb ramp","provider":"owlv2","query":"a photo of a curb ramp","score_threshold":0.05,"source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__gainesville.json b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__gainesville.json
index 10bcce4c..0f30cfb1 100644
--- a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__gainesville.json
+++ b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__gainesville.json
@@ -1 +1 @@
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\ No newline at end of file
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photo of a curb ramp","provider":"owlv2","query":"a photo of a curb ramp","score_threshold":0.05,"source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__manual_gold.json b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__manual_gold.json
index b08c217b..613e52c2 100644
--- a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__manual_gold.json
+++ b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__manual_gold.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__morgantown.json b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__morgantown.json
index 61015d79..b7619c73 100644
--- a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__morgantown.json
+++ b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__morgantown.json
@@ -1 +1 @@
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\ No newline at end of file
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photo of a curb ramp","provider":"owlv2","query":"a photo of a curb ramp","score_threshold":0.05,"source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__paterson.json b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__paterson.json
index 6dd1fa0c..9f7869e6 100644
--- a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__paterson.json
+++ b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__paterson.json
@@ -1 +1 @@
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\ No newline at end of file
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photo of a curb ramp","provider":"owlv2","query":"a photo of a curb ramp","score_threshold":0.05,"source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__richmond.json b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__richmond.json
index 30a7fd3a..db85f2e7 100644
--- a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__richmond.json
+++ b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__richmond.json
@@ -1 +1 @@
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\ No newline at end of file
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photo of a curb ramp","provider":"owlv2","query":"a photo of a curb ramp","score_threshold":0.05,"source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__sao_paulo.json b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__sao_paulo.json
index 71fe251c..44e999e1 100644
--- a/benchmark/model_detections/google__owlv2-large-patch14-ensemble__sao_paulo.json
+++ b/benchmark/model_detections/google__owlv2-large-patch14-ensemble__sao_paulo.json
@@ -1 +1 @@
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\ No newline at end of file
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photo of a curb ramp","provider":"owlv2","query":"a photo of a curb ramp","score_threshold":0.05,"source_max_edge":4096,"tile":true,"views":[[0.0,-30.0,90.0,90.0,1024,1024],[60.0,-30.0,90.0,90.0,1024,1024],[120.0,-30.0,90.0,90.0,1024,1024],[180.0,-30.0,90.0,90.0,1024,1024],[240.0,-30.0,90.0,90.0,1024,1024],[300.0,-30.0,90.0,90.0,1024,1024]]}}
\ No newline at end of file
diff --git a/benchmark/model_detections/y11l_pano__annapolis.json b/benchmark/model_detections/y11l_pano__annapolis.json
index a2bb7dea..27d0c6f2 100644
--- a/benchmark/model_detections/y11l_pano__annapolis.json
+++ b/benchmark/model_detections/y11l_pano__annapolis.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11l_pano__bend.json b/benchmark/model_detections/y11l_pano__bend.json
index 07b04861..6eb93c7f 100644
--- a/benchmark/model_detections/y11l_pano__bend.json
+++ b/benchmark/model_detections/y11l_pano__bend.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11l_pano__budapest_district5.json b/benchmark/model_detections/y11l_pano__budapest_district5.json
index 5c2410e4..12a59be3 100644
--- a/benchmark/model_detections/y11l_pano__budapest_district5.json
+++ b/benchmark/model_detections/y11l_pano__budapest_district5.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11l_pano__clovis.json b/benchmark/model_detections/y11l_pano__clovis.json
index a66b8f06..f8614ca8 100644
--- a/benchmark/model_detections/y11l_pano__clovis.json
+++ b/benchmark/model_detections/y11l_pano__clovis.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11l_pano__gainesville.json b/benchmark/model_detections/y11l_pano__gainesville.json
index 08f1cec8..b7316a05 100644
--- a/benchmark/model_detections/y11l_pano__gainesville.json
+++ b/benchmark/model_detections/y11l_pano__gainesville.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11l_pano__manual_gold.json b/benchmark/model_detections/y11l_pano__manual_gold.json
index 9cf8b6a0..f625ab8a 100644
--- a/benchmark/model_detections/y11l_pano__manual_gold.json
+++ b/benchmark/model_detections/y11l_pano__manual_gold.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11l_pano__morgantown.json b/benchmark/model_detections/y11l_pano__morgantown.json
index 530d611d..04fa9b95 100644
--- a/benchmark/model_detections/y11l_pano__morgantown.json
+++ b/benchmark/model_detections/y11l_pano__morgantown.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11l_pano__paterson.json b/benchmark/model_detections/y11l_pano__paterson.json
index b9781434..db70ee30 100644
--- a/benchmark/model_detections/y11l_pano__paterson.json
+++ b/benchmark/model_detections/y11l_pano__paterson.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11l_pano__richmond.json b/benchmark/model_detections/y11l_pano__richmond.json
index 5341ddcf..79ccce36 100644
--- a/benchmark/model_detections/y11l_pano__richmond.json
+++ b/benchmark/model_detections/y11l_pano__richmond.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11l_pano__sao_paulo.json b/benchmark/model_detections/y11l_pano__sao_paulo.json
index 46bf5fae..34895dc2 100644
--- a/benchmark/model_detections/y11l_pano__sao_paulo.json
+++ b/benchmark/model_detections/y11l_pano__sao_paulo.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11x_pano_h200__annapolis.json b/benchmark/model_detections/y11x_pano_h200__annapolis.json
index fa9c970b..60c5ede7 100644
--- a/benchmark/model_detections/y11x_pano_h200__annapolis.json
+++ b/benchmark/model_detections/y11x_pano_h200__annapolis.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11x_pano_h200__bend.json b/benchmark/model_detections/y11x_pano_h200__bend.json
index 18bb462b..57020c16 100644
--- a/benchmark/model_detections/y11x_pano_h200__bend.json
+++ b/benchmark/model_detections/y11x_pano_h200__bend.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11x_pano_h200__budapest_district5.json b/benchmark/model_detections/y11x_pano_h200__budapest_district5.json
index 10478595..72c6221c 100644
--- a/benchmark/model_detections/y11x_pano_h200__budapest_district5.json
+++ b/benchmark/model_detections/y11x_pano_h200__budapest_district5.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11x_pano_h200__clovis.json b/benchmark/model_detections/y11x_pano_h200__clovis.json
index bad18972..64e8f240 100644
--- a/benchmark/model_detections/y11x_pano_h200__clovis.json
+++ b/benchmark/model_detections/y11x_pano_h200__clovis.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11x_pano_h200__gainesville.json b/benchmark/model_detections/y11x_pano_h200__gainesville.json
index cd701623..aeb69ede 100644
--- a/benchmark/model_detections/y11x_pano_h200__gainesville.json
+++ b/benchmark/model_detections/y11x_pano_h200__gainesville.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11x_pano_h200__manual_gold.json b/benchmark/model_detections/y11x_pano_h200__manual_gold.json
index 07fa6f34..826a33dc 100644
--- a/benchmark/model_detections/y11x_pano_h200__manual_gold.json
+++ b/benchmark/model_detections/y11x_pano_h200__manual_gold.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11x_pano_h200__morgantown.json b/benchmark/model_detections/y11x_pano_h200__morgantown.json
index 81a06787..e9323399 100644
--- a/benchmark/model_detections/y11x_pano_h200__morgantown.json
+++ b/benchmark/model_detections/y11x_pano_h200__morgantown.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11x_pano_h200__paterson.json b/benchmark/model_detections/y11x_pano_h200__paterson.json
index c1b4ad7b..c34a6fb2 100644
--- a/benchmark/model_detections/y11x_pano_h200__paterson.json
+++ b/benchmark/model_detections/y11x_pano_h200__paterson.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11x_pano_h200__richmond.json b/benchmark/model_detections/y11x_pano_h200__richmond.json
index a601d1e7..0a8bc562 100644
--- a/benchmark/model_detections/y11x_pano_h200__richmond.json
+++ b/benchmark/model_detections/y11x_pano_h200__richmond.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y11x_pano_h200__sao_paulo.json b/benchmark/model_detections/y11x_pano_h200__sao_paulo.json
index 9a5bf145..ba1c8155 100644
--- a/benchmark/model_detections/y11x_pano_h200__sao_paulo.json
+++ b/benchmark/model_detections/y11x_pano_h200__sao_paulo.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y26_pano__annapolis.json b/benchmark/model_detections/y26_pano__annapolis.json
index 6d20073b..d4eb210b 100644
--- a/benchmark/model_detections/y26_pano__annapolis.json
+++ b/benchmark/model_detections/y26_pano__annapolis.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y26_pano__bend.json b/benchmark/model_detections/y26_pano__bend.json
index 24f0ac12..a74bc0c1 100644
--- a/benchmark/model_detections/y26_pano__bend.json
+++ b/benchmark/model_detections/y26_pano__bend.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y26_pano__budapest_district5.json b/benchmark/model_detections/y26_pano__budapest_district5.json
index 183a7fbc..82d75ae3 100644
--- a/benchmark/model_detections/y26_pano__budapest_district5.json
+++ b/benchmark/model_detections/y26_pano__budapest_district5.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y26_pano__clovis.json b/benchmark/model_detections/y26_pano__clovis.json
index fe2004e8..e542e8f1 100644
--- a/benchmark/model_detections/y26_pano__clovis.json
+++ b/benchmark/model_detections/y26_pano__clovis.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y26_pano__gainesville.json b/benchmark/model_detections/y26_pano__gainesville.json
index 9f58edbc..ac53d5a2 100644
--- a/benchmark/model_detections/y26_pano__gainesville.json
+++ b/benchmark/model_detections/y26_pano__gainesville.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y26_pano__manual_gold.json b/benchmark/model_detections/y26_pano__manual_gold.json
index 1b7cb6a5..ee486710 100644
--- a/benchmark/model_detections/y26_pano__manual_gold.json
+++ b/benchmark/model_detections/y26_pano__manual_gold.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y26_pano__morgantown.json b/benchmark/model_detections/y26_pano__morgantown.json
index 97b07d9d..951246eb 100644
--- a/benchmark/model_detections/y26_pano__morgantown.json
+++ b/benchmark/model_detections/y26_pano__morgantown.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y26_pano__paterson.json b/benchmark/model_detections/y26_pano__paterson.json
index d4fa87cc..5d079573 100644
--- a/benchmark/model_detections/y26_pano__paterson.json
+++ b/benchmark/model_detections/y26_pano__paterson.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y26_pano__richmond.json b/benchmark/model_detections/y26_pano__richmond.json
index b5c4a4b0..5ae20576 100644
--- a/benchmark/model_detections/y26_pano__richmond.json
+++ b/benchmark/model_detections/y26_pano__richmond.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/benchmark/model_detections/y26_pano__sao_paulo.json b/benchmark/model_detections/y26_pano__sao_paulo.json
index cad30f5d..1c1badf3 100644
--- a/benchmark/model_detections/y26_pano__sao_paulo.json
+++ b/benchmark/model_detections/y26_pano__sao_paulo.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/docs/replication.md b/docs/replication.md
index 5f711257..5a21dc64 100644
--- a/docs/replication.md
+++ b/docs/replication.md
@@ -54,10 +54,29 @@ them belongs to a registered leg:
 `rampnet` is a row in every results table and has no file here: it is read from each bundle's
 committed `records.jsonl` and carries no detector signature.
 
-Two tests hold that table up rather than trust it.
+Every one of those files is in **canonical form** — byte-identical to what
+`export_model_cache.py` would write today — which is the difference between a corpus that
+*is* reproducible and one that merely scores the same. It was not, until 2026-08-18: the
+`published_as` field arrived with the Claude legs, so the 108 files exported before it lacked
+it and re-exporting any of them produced a diff with identical detections inside. Bringing
+them up to date needed no cache, because the serialization is deterministic and each file's
+published name was recoverable from the file itself:
+
+```bash
+python scripts/analysis/export_model_cache.py --canonicalize          # report
+python scripts/analysis/export_model_cache.py --canonicalize --write  # apply
+```
+
+That is worth knowing for the next envelope change: **it is not a reason to go find the
+machine that produced each leg.** Only a file whose published name cannot be derived from its
+own contents needs a real re-export, and `--canonicalize` names those rather than guessing.
+`test_every_published_file_is_in_canonical_form` now fails if the corpus drifts again.
+
+Three tests hold that table up rather than trust it.
 `test_the_ledger_count_matches_the_directory` asserts the count, and
 `test_every_published_detections_file_belongs_to_a_registered_leg` asserts the stronger
-property that nothing in the directory is unaccounted for. The second one is why this table
+property that nothing in the directory is unaccounted for; the third is the canonical-form
+check above. The second one is why this table
 exists: **the registry covered 78 of the 112 files.** The YOLO arms and the Claude legs had
 been run, scored, verified and written up, and the one place that is supposed to enumerate
 every model said nothing about them — which is also what the unremarked 78 → 108 jump in the
diff --git a/scripts/analysis/export_model_cache.py b/scripts/analysis/export_model_cache.py
index 54425014..ed244af8 100644
--- a/scripts/analysis/export_model_cache.py
+++ b/scripts/analysis/export_model_cache.py
@@ -40,6 +40,7 @@
 ``.model_cache`` when present, so a fresh clone works with no cache at all.
 """
 import argparse
+import glob
 import json
 import os
 import sys
@@ -199,11 +200,61 @@ def export(cache_dir, out_dir, splits, specs, allow_partial=False, overrides=Non
                 json.dump({"model": label, "published_as": name,
                            "city": city, "signature": sig,
                            "n_panos": len(dets), "n_uncached": missing,
-                           "detections": dets}, fh, separators=(",", ":"), sort_keys=True)
+                           "detections": dets}, fh, **DUMP_KW)
             written.append((label, city, len(dets), missing, os.path.getsize(path)))
     return written, skipped, partial, collisions
 
 
+#: Exactly how a published file is serialized. Any writer must use these, or two
+#: runs that agree on every value still produce different bytes.
+DUMP_KW = {"separators": (",", ":"), "sort_keys": True}
+
+
+def canonical_bytes(payload):
+    """The published form of one export's payload."""
+    return json.dumps(payload, **DUMP_KW).encode("utf-8")
+
+
+def canonicalize(out_dir=PUBLISHED_DIR, write=False):
+    """Bring published files up to the current envelope, without a cache.
+
+    The detections are never touched -- only the metadata header around them. This
+    exists because the header gains fields over time: ``published_as`` arrived with
+    the Claude legs (#122), so the 110 files exported before it did not have it, and
+    re-running the exporter on any of them would have produced a file that differed
+    from the committed one. That is the thing docs/replication.md promises does not
+    happen.
+
+    The alternative was re-exporting from ``.model_cache``, which would mean finding
+    the machine that produced each leg -- Hyak for the open detectors, makelab2 for
+    the YOLO trio. Unnecessary: the serialization is deterministic (``DUMP_KW``), and
+    for every one of those files the published name is recoverable from the file
+    itself, so the result is byte-identical to what a real re-export would write.
+
+    Returns ``(changed, unfixable)``. ``unfixable`` lists files whose published name
+    cannot be derived -- ``slug(model)`` disagreeing with the filename means the file
+    was published under a name only the run that made it knew, and guessing it is
+    exactly the silent rename this whole mechanism exists to prevent.
+    """
+    changed, unfixable = [], []
+    for path in sorted(glob.glob(os.path.join(out_dir, "*__*.json"))):
+        raw = open(path, "rb").read()
+        payload = json.loads(raw.decode("utf-8"))
+        stem = os.path.basename(path).rpartition("__")[0]
+        if "published_as" not in payload:
+            if slug(payload["model"]) != stem:
+                unfixable.append((os.path.basename(path), payload["model"]))
+                continue
+            payload["published_as"] = payload["model"]
+        out = canonical_bytes(payload)
+        if out != raw:
+            changed.append(os.path.basename(path))
+            if write:
+                with open(path, "wb") as fh:
+                    fh.write(out)
+    return changed, unfixable
+
+
 def verify(cache_dir, out_dir, splits, specs, overrides=None, publish_as=None):
     """Do the exported detections score identically to the cached ones?
 
@@ -300,8 +351,23 @@ def main(argv=None):
                         "legs that would otherwise both write claude-sonnet-5__<split>.json. "
                         "Names ONE leg, so it takes a single --models spec. The SAME value "
                         "must be passed to --verify.")
+    p.add_argument("--canonicalize", action="store_true",
+                   help="Bring the published files up to the current metadata "
+                        "envelope and exit. Touches no detections and needs no "
+                        "cache. Reports what would change; add --write to apply.")
+    p.add_argument("--write", action="store_true",
+                   help="With --canonicalize, actually rewrite the files.")
     args = p.parse_args(argv)
 
+    if args.canonicalize:
+        changed, unfixable = canonicalize(args.out, write=args.write)
+        for name, model in unfixable:
+            print(f"  ✗ {name}: published under a name not derivable from "
+                  f"model {model!r} — re-export it from the cache that made it")
+        verb = "rewrote" if args.write else "would rewrite"
+        print(f"{verb} {len(changed)} file(s); {len(unfixable)} need a real re-export")
+        return 1 if unfixable else 0
+
     splits = [s.strip() for s in args.splits.split(",") if s.strip()]
     specs = [s.strip() for s in args.models.split(",") if s.strip()]
     overrides = {"tiling": args.tiling, "yolo_imgsz": args.yolo_imgsz,
diff --git a/tests/test_export_model_cache.py b/tests/test_export_model_cache.py
index 690889e8..8633dad1 100644
--- a/tests/test_export_model_cache.py
+++ b/tests/test_export_model_cache.py
@@ -337,6 +337,50 @@ def test_the_ledger_count_matches_the_directory():
         "the 'Status by input' table's file count disagrees with the directory")
 
 
+def test_every_published_file_is_in_canonical_form():
+    """A regenerated copy must be provably identical, not merely equivalent.
+
+    This is the strong version of that promise and it costs nothing to check: every
+    committed file must equal its own canonical re-dump, so the corpus cannot drift
+    from what the exporter writes. It caught the drift it was written for -- 108 of
+    114 files predated the `published_as` field, so re-exporting any of them would
+    have produced a diff with identical detections inside.
+    """
+    stale = em.canonicalize(em.PUBLISHED_DIR, write=False)[0]
+    assert not stale, (
+        f"{len(stale)} published file(s) are not what the exporter would write, "
+        f"e.g. {stale[:3]} — run `python scripts/analysis/export_model_cache.py "
+        f"--canonicalize --write`")
+
+
+def test_canonicalize_never_touches_detections():
+    """It exists to edit the metadata envelope. If it could rewrite a detection it
+    would be a way to silently alter published results without a cache."""
+    before = {}
+    for name in os.listdir(em.PUBLISHED_DIR):
+        if name.endswith(".json"):
+            with open(os.path.join(em.PUBLISHED_DIR, name), encoding="utf-8") as fh:
+                before[name] = json.load(fh)["detections"]
+    changed, unfixable = em.canonicalize(em.PUBLISHED_DIR, write=False)
+    assert not changed and not unfixable          # already canonical, so a no-op
+    for name, dets in before.items():
+        with open(os.path.join(em.PUBLISHED_DIR, name), encoding="utf-8") as fh:
+            assert json.load(fh)["detections"] == dets, name
+
+
+def test_every_published_file_declares_the_name_it_is_published_under():
+    """`model` is the cache label and `published_as` is the filename. They differ
+    exactly when a pin is involved, so a file that omits the second is a file whose
+    identity has to be inferred from its own filename."""
+    for name in os.listdir(em.PUBLISHED_DIR):
+        if not name.endswith(".json"):
+            continue
+        with open(os.path.join(em.PUBLISHED_DIR, name), encoding="utf-8") as fh:
+            payload = json.load(fh)
+        assert "published_as" in payload, name
+        assert em.slug(payload["published_as"]) == name.rpartition("__")[0], name
+
+
 def test_every_published_leg_is_named_in_the_ledger():
     """A published artifact nobody documented is indistinguishable from a stray
     file. Each distinct model stem under model_detections/ must appear by name in