Add operator hard-negative detection matrix

docs/TODO.md

@@ -105,7 +105,8 @@ This file now starts with the current implementation status. Older preparation/b
 - [x] Train and benchmark the first tile-level local YOLO candidate on Tower through the persisted QA/QC matrix.
 - [x] Calibrate confidence, IoU and model selection against additional local orthophoto/reference samples beyond Geel/Mol/Turnhout.
 - [x] Add negative/background AOIs to the operator sample corpus and train an expanded local tile-level YOLO candidate.
-- [ ] Add a hard-negative model-quality pass with more sparse/background AOIs, balanced tile export and explicit false-positive scoring.
+- [x] Add a hard-negative model-quality pass with sparse/background AOIs and explicit false-positive scoring.
+- [ ] Train a hard-negative-balanced YOLO candidate and rerun dense QA plus background false-positive matrices.
 - [ ] Find or train a materially stronger aerial/Kempen building model candidate; `geointel-building-yolov8n-expanded160e50-pt` is the best current dense-AOI candidate but still too weak and too noisy for a V1 default.
 
 ## Sprint 8 status