docs: record Mol benchmark decision

2026-07-14 12:40:11 +02:00
parent 9f61037794
commit 5db93a9530
7 changed files with 57 additions and 7 deletions
@@ -28,7 +28,8 @@ This file now starts with the current implementation status. Older preparation/b
 - [x] Visually review Mol Postel and Donk false-positive/false-negative evidence, classify the dominant error modes and only then decide whether another model-training pass is justified.
 - [x] Clip detection QA populations to persisted raster/tile coverage and add box-to-footprint matching diagnostics before reconsidering model training.
 - [x] Add a coverage-aware Mol multi-zone benchmark report with explicit positive-zone, per-zone collapse, reference-coverage and pure-empty background gates.
- [ ] Execute the refreshed coverage-aware Mol operational benchmark against the active local model and record the resulting retain/review decision.
+- [x] Execute the refreshed coverage-aware Mol operational benchmark against the active local model and record the resulting retain/review decision.
+- [ ] Complete manual decisions for the generated 48 false-negative and 48 false-positive review cards before constructing any new training corpus.
 - [x] Backend FastAPI foundation, health endpoint and service structure.
 - [x] React/TypeScript frontend foundation and MapLibre workbench.
 - [x] Map layer visibility, opacity and feature property inspection.