Expand operator hard-negative AOIs

docs/TODO.md

@@ -442,5 +442,13 @@ This file now starts with the current implementation status. Older preparation/b
 - [x] Report sample coverage, validation coverage, repeated hard-negative pressure and YOLO label area integrity.
 - [x] Wire the audit script into the readiness syntax gate.
 - [x] Use live audit output to decide whether the next model pass needs more positive AOIs, label cleanup or unique hard negatives.
-- [ ] Add more unique background/hard-negative AOIs before repeating hard-negative-balanced YOLO training.
+- [x] Add more unique background/hard-negative AOIs before repeating hard-negative-balanced YOLO training.
 - [ ] Keep `yolo-building-tile-expanded160` as the clean current training baseline; avoid promoting r4/r8 repeat-heavy datasets as defaults.
+- [ ] Regenerate Tower operator samples, export a new unique-hard-negative tile dataset and rerun the dataset audit before training.
+
+# Sprint 147 - Unique hard-negative AOI expansion
+
+- [x] Expand the documented operator background candidates from 3 to 9 unique AOIs.
+- [x] Keep every new background AOI explicit, `allow_empty_reference=True`, and `sample_role='background_candidate'`.
+- [x] Add test coverage for minimum background candidate count, unique centers and regional spread.
+- [ ] Prepare the new samples on Tower and build a fresh hard-negative tile dataset.