The recommended detection profile showed operators precision 0.614, recall
0.606 and F1 0.607. Those three numbers appear nowhere in this repository
except the file that publishes them and a test that pinned them as literal
strings. The only recorded evaluation of that model at that operating point —
tile 512, overlap 64, threshold 0.15, the exact key its promotion report
recommended — reported 0.590, 0.577 and 0.582. The published figures were about
two and a half points more flattering than anything that was measured, on the
profile labelled "aanbevolen", and the test made sure nobody would correct
them. They now carry the measured values.
Worse in kind: the conservative profile reported "gemeten achtergrondfouten 0".
Its nine-sample hard-negative matrix at threshold 0.35 recorded 198 background
detections with 55 in the worst sample. The one number that tells an operator
whether a high-precision model invents buildings on empty terrain said zero
where the evidence said 55.
Those zeros are not simply wrong everywhere, which is why the fix is not just a
number. The other two profiles genuinely produced zero — against a strict
pure-empty gate of three samples, a different and much weaker test than the
nine-sample hard-negative matrix. Printing 0, 0 and 55 side by side invites a
comparison the evidence does not support, so each profile now states its gate,
its background sample count and the evaluation behind its figures, and the
panel shows them.
A test refuses any published figure that does not appear in the evidence
record, with a negative control so it cannot pass by matching nothing. Pinning
the numbers as literal strings is what let an unsourced precision survive; that
assertion is gone.
Also ignoring .codex-artifacts/ — ~300 MB of the rejected SAM2 and
edge-alignment trials plus a deploy bundle. Kept on disk, out of the repository.
No credentials in it; the two token scripts generate from settings.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
An ArcGIS layer without supportsPagination accepts resultOffset and ignores it,
answering every page with the first one. The VHA profile reader advanced its
offset by the page length and stopped at the announced count, so for a count
that is a multiple of the page size it collected N copies of page one — and its
completeness check, len(features) == candidate_count, passed. Four announced
records became four stored records, two of them duplicates, filed under an
official provenance. That is the substitution bounded acquisition exists to
prevent, arriving through the front door.
The reader now refuses a record it already collected. It fails rather than
silently dropping the duplicate: a provider that cannot page is a provider
whose count proves nothing, so a smaller-but-clean result would still be
unverifiable. Its watercourse-name loop was worse — a bare `while True` that
ended only when the provider stopped setting exceededTransferLimit, with names
deduplicated by code so a stuck provider produced no visible change while the
requests continued. It now refuses a repeated page body, and both loops have
the page budget the sibling readers already had.
Those siblings turned out to be fine. GRB and official vector already refuse a
repeated page URL, bound the page count, and deduplicate on feature identity —
but none of it had a test, so none of it was known to work. Exercised now,
including the case where distinct URLs defeat the loop check and the budget is
the only backstop. A duplicate across two genuinely different pages is kept
once rather than failing, because a cursor over a changing table produces that
legitimately.
Also: _bash_path fell back to the raw path whenever wslpath failed, except on
timeout, which propagated and reddened the suite when starting WSL took more
than ten seconds under load.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Two problems of the same shape: information about *why* something failed being
replaced by something vaguer.
get_dataset_geojson wrapped the JSON parse, the metadata read, the CRS
resolution and the canonicalisation in one try and reported all of it as
"Stored dataset is not valid JSON" with a 500. An operator whose dataset had an
unusable CRS was sent to inspect a file that parses perfectly well, and the
canonicaliser's own AppError — with its code and its status — never reached
them. Only the parse is now inside that handler; everything after it keeps the
error it raised, and a genuine bug becomes a distinct 500 rather than a
mislabelled client error. A guard finds the same shape elsewhere: catching
Exception around a call into another component and relabelling what it
reported. Wrapping one's own private helper stays legitimate and the guard
says so.
The redirect policy was split without anyone saying so. Two acquisition
services rejected every redirect through a hand-rolled opener, while eight
allowed a same-origin one through the shared guard — and only the latter
checked where the response came from. Both live in the guard now, and the
strict path uses the rejecting handler rather than the guard's after-the-fact
check: objecting to response.url means urllib already opened the connection and
read the body, which for a metadata endpoint is the whole attack. That was a
weakening I introduced in this same commit's first draft.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
scripts/evaluate_belgium_building_candidate.py freezes its post-processing
before the protected test — NMS IoU and a containment threshold selected during
calibration, defaulting to 1.0. The runtime applied a hardcoded 0.85, so a
promoted candidate was served under suppression its evaluation never measured
and dropped detections the gate had counted. Neither report showed the
difference. That constant was mine, added without noticing the evaluation
pipeline already had a tuned value for the same concept.
Containment is now configuration, recorded on every run beside the duplicate
IoU threshold, so an operator can serve a candidate at the value it was gated
at and afterwards see which value produced a given score.
Two runs that post-processed differently produced different candidate sets from
the same model output, so the comparison endpoint refuses to rank them. Runs
recorded before those values were persisted carry none, and absence is not
treated as a difference.
The remaining gap is deliberate and documented rather than closed: the gate
scores the model on its protected test set, the workbench scores the whole
pipeline including coverage clipping and the tile-edge filter. A promoted
candidate will not reproduce its gate F1 exactly, and pretending otherwise
would be the worse answer.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Two defects of the same kind: work that is supposed to be bounded is not.
The analysis worker selected queued jobs and then set them to running in a
second statement. A restarted process overlapping the previous one, or a second
replica, could both select the same row and both start tiled GPU inference on
it — duplicate analysis runs and double the GPU load. The AOI worker beside it
already claims with FOR UPDATE SKIP LOCKED; this uses a conditional update,
which is the same guarantee in one statement. run_once now reports jobs it
actually claimed rather than jobs it looked at.
urlopen follows redirects, so although every acquisition URL is built from
settings and cannot be steered by a request payload, a misconfigured or
compromised upstream could send the runtime to the loopback interface, to
another container on the compose network, or to a cloud metadata endpoint — and
the bytes would then be persisted under an official provenance. That is exactly
the substitution the product forbids. All eight fetch sites now open through a
guard that refuses private, loopback and link-local destinations (resolving the
host first, so a DNS name cannot hide one) and refuses a redirect that leaves
the configured origin or downgrades from HTTPS.
The guard is proven by calling the services' own fetch paths, not by grepping
for the call: every existing acquisition test injects an opener, which bypasses
it by design.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
The README's architecture diagram and stack list promised Redis + RQ. There is
no such thing in this codebase: redis_url is a settings field nothing reads,
rq is not a dependency, and the only worker is an asyncio poller over a
Postgres job table. Describe what exists.
API_CONTRACTS and KNOWN_LIMITATIONS gain the rules a reader needs to interpret
a result: deterministic confidence-ranked matching, the precision/recall curve,
the three flood-hazard cell populations, the sub-cell selection fallback, the
whole-feature object count next to clipped area metrics, and the required
manifest CRS. The new limitations are stated as limits rather than buried:
raster analysis has no sub-cell precision, and the object count is not
fractional.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
