# Phase 1 command and result ledger

Captured: 2026-08-01  
Audited repository baseline: `0c019bb22f816db1e4b7a68379bcad08924d9a21`  
Branch: `codex/geointel-accuracy-program`

This ledger records the commands and claim boundaries behind the retained
evidence. JSON, JUnit, SQL and full text logs in this directory are the source
of truth when this summary and a raw artifact differ.

## Repository and static inventory

```powershell
python scripts/run_accuracy_phase1_baseline.py --output-dir artifacts/evidence/accuracy/P1
```

Result: completed. The baseline found 2,495 tracked files, including a tracked
`geointel/` mirror with 1,153 files; 68 paired files differ from root. No model
checkpoint is tracked in the local checkout. The mirror is excluded by the root
`.dockerignore`; the residual risk is source/import/maintenance ambiguity, not
official all-in-one build-context inclusion.

Evidence:

- `phase1-baseline-summary.json`
- `repository-inventory.json`
- `local-artifact-inventory.json`
- `static-risk-signals.json`

## Deterministic contract reproductions

```powershell
python scripts/reproduce_accuracy_phase1_findings.py
```

Result: 7 of 7 expected violations reproduced. They cover cross-theme coverage
contamination, metres-as-degrees buffering, Lambert-as-4326 persistence,
caller-spoofed source authority, mutable-name model scope, mutable-name legal
scope and silently ignored Area PATCH geometry.

Evidence: `forensic-reproductions.json`.

## Tower runtime, database and storage references

The collector was streamed into the running `geointel` container and executed
with read-only SQL and a 30-second statement timeout:

```text
docker exec -i geointel env PYTHONPATH=/app/backend python -
```

Result:

- Python 3.11.2, PyTorch 2.11.0+cu128, CUDA 12.8, Ultralytics 8.4.99;
- NVIDIA GeForce RTX 4080 SUPER visible on `cuda:0`;
- Alembic head `202607260001`;
- 5,816 direct database storage references checked, 0 missing;
- four Geel detections contain Lambert-domain coordinates while the geometry
  column reports SRID 4326;
- no database or storage row was modified.

A broader recursive `audit_data_operations.py` storage scan was stopped by its
244-second execution timeout and produced no retained result. It is not counted
as a pass. The bounded, direct-reference collector above completed and is the
only storage-completeness claim made here.

Evidence:

- `tower-runtime-database-snapshot.json`
- `tower-runtime-database-snapshot-detailed.json`

## Real GPU inference smoke

The read-only collector used the production `YoloDetectionAdapter`, the active
model and one existing Geel tile:

```text
python - --model-path /app/models/geointel-building-yolov8s-smallbld-minpx3-img640-ft30.pt \
  --tile-path /app/storage/tiles/cb80638d-dbef-48ac-b19c-cec7c3efc96e/ae0ff76d-70c0-404f-b777-54d14517179a/b191c968-7d56-4e0d-afbb-8b5baaa62470/tile_0000.tif \
  --manifest-path /app/storage/tiles/cb80638d-dbef-48ac-b19c-cec7c3efc96e/ae0ff76d-70c0-404f-b777-54d14517179a/b191c968-7d56-4e0d-afbb-8b5baaa62470/manifest.json \
  --confidence 0.5 --image-size 640 --max-detections 1000 --device cuda:0 --seed 20260801
```

Result: passed; 17 raw building detections; 0.883694486 s synchronized
inference; model SHA-256
`a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1`.

Claim boundary: this proves one runtime execution. It does not prove that any
box is correct, that confidence is calibrated, or that the model generalizes.

Evidence: `tower-gpu-inference-smoke.json`.

## ML/data-lineage inventory

The bounded collector read V56/V58/V62/V66 plus model, checkpoint, report and
manifest metadata from the mounted Tower volume:

```text
docker exec -i geointel python - --app-root /app
```

Result:

- 26 model assets, 229 training checkpoints, 424 training JSON reports and
  36 operator manifests inventoried;
- V56 has 180 AOIs and 0 completed human reviews;
- three pure-empty background-test AOIs: Flanders 2, Wallonia 1, Brussels 0;
- zero exact cross-split raster-hash duplicates;
- bounded 64-bit dHash screen: 180 rasters, minimum Hamming distance 17,
  zero cross-split pairs at or below 4;
- minimum cross-split AOI bbox distance 95.720336 m and 24 pairs below 2 km;
- V58/V62 evidence is calibration-only; at threshold 0.15 aggregate F1 is
  0.512905 while Flanders recall and F1 are 0;
- no protected-test, background-test promotion or national-release evidence.

Claim boundary: exact/dHash and bbox-distance screens do not establish
municipality, flight-strip, instance, semantic or imagery-edition independence.

Evidence: `tower-ml-data-lineage-snapshot.json` and
`tower-key-artifact-hashes.json` (V62 best/last checkpoints and V56 tile audit).

## Backend tests

### Full root-context suite

```powershell
$env:PYTHONPATH='C:\Projects\geointel\backend;C:\Projects\geointel'
python -m pytest backend/tests -q -p no:cacheprovider \
  -W error::DeprecationWarning \
  --junitxml=artifacts/evidence/accuracy/P1/backend-full-suite.junit.xml
```

Result: exit 1; 1,180 passed and 17 failed in 70.63 seconds. The 17 failures are
stale source/contract assertions, including expectations that conflict with the
new explicit user-selected model flow. They remain release-blocking until
replaced with reviewed behavior tests.

Evidence:

- `backend-full-suite.txt`
- `backend-full-suite.junit.xml`

### Actual backend CI working directory

```powershell
cd backend
python -m pytest -W error::DeprecationWarning
```

Result: exit 2 during collection; 1,194 items collected plus one import error:

```text
ModuleNotFoundError: No module named 'scripts.render_operator_polygon_label_qa'
```

Evidence: `backend-ci-entrypoint.txt`.

### Phase 1 tooling

```powershell
python -m pytest tests/test_accuracy_phase1_baseline.py -q -p no:cacheprovider
```

Result: 4 passed.

Evidence: `phase1-tooling-tests.txt`.

## Lint

```powershell
python -m ruff check scripts/collect_accuracy_phase1_inference_smoke.py \
  scripts/collect_accuracy_phase1_ml_lineage.py \
  scripts/collect_accuracy_phase1_runtime.py \
  scripts/reproduce_accuracy_phase1_findings.py \
  scripts/run_accuracy_phase1_baseline.py tests/test_accuracy_phase1_baseline.py
```

Result: all new Phase 1 code passed.

```powershell
python -m ruff check backend scripts tests
```

Result: exit 1; 112 findings: E402 13, E701 2, E702 69, F401 23, F403 1,
F811 2 and F841 2.

Evidence:

- `repository-ruff-baseline.txt`
- `repository-ruff-baseline.json`

## Frontend

```powershell
cd frontend
npm run test:unit
npm run typecheck
npm run build
```

Results:

- Vitest: 16 files, 51 tests passed;
- TypeScript typecheck: passed;
- production build: passed, 1,896 modules transformed.

The attempted generic `npm test -- --run` failed because no `test` script
exists; the configured command is `test:unit`. The test strategy also calls
for lint, but `npm run lint` fails with `Missing script: "lint"`.

Evidence:

- `frontend-vitest.txt` (failed non-existent generic command, retained)
- `frontend-vitest-unit.txt` (correct configured command, passed)
- `frontend-typecheck.txt`
- `frontend-build.txt`
- `frontend-lint.txt`

## API, migrations and golden QA

```powershell
python scripts/audit_api_contracts.py
```

Result: 147 implemented routes match documentation; 10 explicitly tracked
non-envelope endpoints.

Evidence: `openapi-contract-audit.txt`.

```powershell
cd backend
python -m alembic heads
python -m alembic upgrade head --sql
```

Result: one head, `202607260001`; complete offline upgrade rendered 496 SQL/log
lines. This is not a local live-PostGIS migration test.

Evidence:

- `alembic-heads.txt`
- `alembic-offline-upgrade.sql`

```powershell
python scripts/run_golden_qa_benchmark.py --json
```

Result: two runs have semantically identical metric results but different file
hashes because run identities use UUID4.

Evidence:

- `golden-qa-run-1.json`
- `golden-qa-run-2.json`
- `golden-qa-reproducibility.json`

## Explicitly not executed as a success gate

- no protected test or background-test portfolio was opened;
- no training, calibration fitting, checkpoint promotion or active-model change;
- no label was accepted on behalf of a human reviewer;
- no production database migration or data repair;
- no dataset, checkpoint, cache, output or user-owned untracked file deleted,
  rewritten or moved;
- no segmentation, SAM or solar asset was inferred to be production-ready from
  file presence.