Add detection model promotion report

docs/CODEX_EXECUTION_LOG.md

@@ -1,3 +1,25 @@
+## Sprint 143 Detection model promotion decision report (2026-07-08)
+
+Changed:
+- Added `scripts/build_detection_model_promotion_report.py` as operator-only evidence tooling.
+- The script combines a positive-AOI `calibration_evidence_portfolio.json` with one or more `hard_negative_matrix_summary.json` files.
+- Candidate rows are grouped by `model_asset_id`, `tile_size`, `tile_overlap` and `threshold`.
+- Promotion gates are explicit:
+  - minimum positive sample count
+  - minimum background sample count
+  - minimum mean positive F1
+  - maximum background detections per sample
+- Added readiness `py_compile` coverage for the new script.
+- Documented the Tower command in `scripts/README.md`.
+
+Tested:
+- Red step: `python -m pytest backend\tests\test_sprint143_detection_model_promotion_report.py -q` failed because the report script did not exist.
+- `python -m pytest backend\tests\test_sprint143_detection_model_promotion_report.py -q` (`1 passed`)
+
+Open:
+- Run the report against the regenerated 7-AOI positive portfolio and live hard-negative summaries on Tower.
+- Use the report as a promotion gate only; it must not mutate the active YOLO model configuration.
+
 ## Sprint 141 Expanded positive-AOI matrix and portfolio metadata hardening (2026-07-08)
 
 Changed:

docs/TODO.md

@@ -430,5 +430,6 @@ This file now starts with the current implementation status. Older preparation/b
 - [x] Run fresh positive-AOI matrix coverage for Balen, Herentals and Westerlo.
 - [x] Preserve model/tile provenance in calibration evidence bundle summaries.
 - [x] Prevent same-threshold calibration evidence responses from overwriting each other in multi-model portfolios.
+- [x] Add a model promotion decision report that combines positive-AOI score with hard-negative false-positive pressure.
 - [ ] Add more AOIs after the tile-level baseline so the next local model attempt is not limited to Geel/Mol/Turnhout.
 - [ ] Add negative/background AOIs so the next tile dataset is not all positive tiles.