Detection QA reports a precision/recall curve, average precision and a
calibration sweep; segmentation QA reported a single operating point. Both rank
their outputs by confidence, so the same view applies, and the asymmetry meant
the two panels answered different questions about comparable runs — an
inconsistency introduced when detection gained the curve.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
The review vocabulary already separates a model error from a reference gap,
because the product's position is that official footprints are not
automatically perfect ground truth. Those verdicts were only counted. An
operator who inspected forty false positives and established that twelve are
buildings the reference simply lacks still saw a precision counting all forty
against the model — a number they had personally disproved, on the panel where
they disproved it.
Applying the verdicts gives an adjudicated score reported next to the raw one,
so nothing is quietly improved. Not being able to judge is not evidence in the
model's favour, so uncertain and obscured verdicts keep counting, as does a
decision from a later release that this runtime does not recognise.
Because part of the evidence is usually still unreviewed, the honest form is an
interval rather than a single corrected number: pessimistic assumes every
unreviewed finding is a model error, optimistic assumes none is, and the
headline equals the pessimistic reading so a partly reviewed check never
presents as a settled one.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Threshold calibration ran the model over every tile once per threshold — three
GPU passes to compare 0.50, 0.25 and 0.15 on a hundred-tile raster. The answer
is already in a single run at the lowest value: detections above a higher cut
are a subset of it, and duplicate suppression walks candidates in descending
confidence, so a lower-confidence box can never displace a higher-confidence
one. The kept set above any cut is identical whichever threshold the run used,
which is what makes one pass sufficient rather than merely cheaper.
QA now takes calibration_thresholds and reads each operating point off the same
precision/recall walk it already performs, marking the F1-optimal cut. The lab
runs inference once and fills its table from the sweep.
The contract test asserted the per-threshold loop by name, pinning the waste it
was meant to describe. It now states what calibration owes an operator: a row
per requested threshold, from one run.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Extracted for its error paths, not its size. Every step can fail or return
nothing, and each outcome has to leave the operator with a status that says
where the chain stopped — a workflow reporting "afgerond" after a step produced
nothing tells them a result exists when it does not. Inline in the component,
none of that was exercised; it now has fourteen tests covering each stopping
point, both rejection kinds, the reuse path and the preconditions.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Corner tracking for a two-click rectangle lived inline in the component and
was never exercised. The rule worth pinning is that a first corner yields no
rectangle at all: acting on it would analyse a zero-width area.
The hook holds only interaction state — drawing mode, placed corner, the
coordinate fields. What happens with a finished rectangle stays in the
workspace, which owns retiring stale results and starting the analysis.
Injecting that would have made the hook depend on values declared after it,
which is what a first attempt at a wider extraction ran into.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
MapWorkspace held five near-identical useMemo blocks deciding which raster
image the map draws under the active theme — terrain, flood depth, thematic
raster, WALOUS land cover and bathymetry. Each filtered partitions by source
name, read bbox_epsg4326 and assembled the same overlay shape, so the parts
that genuinely differ per theme were buried in the repetition.
One builder makes the rule testable and leaves only the source, the label and
the opacity varying. A raster whose bounds are unusable is now skipped rather
than drawn from a partial bbox: an overlay in the wrong place is worse than no
overlay.
The legend asked "are these thematic or WALOUS overlays" by inspecting two of
the five lists. That is a property of the source, so it says so directly.
Two contract tests needed fixing rather than repointing. One asserted
`"api" not in source.lower()`, which the new hook name useMapImageOverlays
matches inside "useM-api-mageOverlays" — as would rapid, capital or therapy.
The contract is that this component talks to no API client, so it now says
that.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
MapWorkspace.tsx opened with ~590 lines of theme catalogue, dataset matching
and label formatting above a 3.200-line component. None of it is React, all of
it is independently testable, and both render paths read from it, so it belongs
beside the pure helpers that already live in mapWorkspaceUtils.
The contract tests that read MapWorkspace.tsx would have gone red for a move
that changes no behaviour at all — 24 of them. That is the brittleness the
frontend_contract helper exists to remove, so it gains read_map_workspace():
the workspace is one feature spread over several modules, and a contract
belongs to the feature rather than to whichever file currently holds it.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
/detection/runs/{id}/detections and its GeoJSON sibling returned every
persisted detection, as did the segmentation equivalents. A regional run holds
tens of thousands, and these are the endpoints the results table and the map
overlay call after every run.
They now take limit and offset, default to 2.000, and report total, limit,
offset and truncated so the complete population stays visible while what is
transferred does not. The GeoJSON responses carry the same window in a
geointel_result_window foreign member.
Rows are ordered by confidence, so a capped overlay draws the strongest
detections rather than an arbitrary slice, and the lab says how many of how
many are being shown rather than silently presenting a page as the whole run.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
evidence_geojson emitted one feature per false positive, one per false negative
and two per match, with no limit. A regional check of 40k detections against 45k
reference footprints produced well over a hundred thousand features in a single
response, plus one warning string per unresolvable identifier. The endpoint the
entire review workflow depends on therefore failed exactly where review matters
most.
What to draw is now decided before any geometry is fetched, so the query work is
proportional to the result rather than to the size of the check — previously
130k geometries were resolved through an IN clause holding every identifier in
the check, to then discard most of them.
The budget is split between misses and false positives in proportion to their
populations with at least one of each, rather than by strict priority, which
would mean a check with 50.000 misses and three false positives never showed
one. Confirmations fill what remains, and a match is kept or dropped as a pair
because half a match is not reviewable evidence.
limit_evidence and evidence_role_counts are removed: plan_evidence supersedes
them, and helpers kept alive only by their own tests read like a contract.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
The comparison hook runs before the selection state is declared in App, so the
selection is read through a getter at the moment the run starts rather than
captured at render. The panel gains the modified count, which until now was
folded into removed plus added.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
The backend now says when a result covers a different area than was drawn, or
when a score belongs to one confidence cut only. None of that helps an
operator while it stays in the response body.
- the raster selection adapters carry the model-coverage and widened-cell
warnings into the map panel and mark the result an estimate when either
applies, so an existing warning slot renders them;
- the map workspace shows the selection-edge disclosure next to the object
count;
- the detection panel shows average precision and the F1-optimal threshold
beside the single-threshold figures, and the box-versus-footprint
interpretation when candidates are detector boxes.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
