The feedback loop, per product decision (option a): tags feed STATISTICS only.
A human reads the rate and re-tunes a camera deliberately - the tag never
adjusts edge sensitivity on its own (no silent behavior change in a safety
system).
- POST /events/{id}/false-positive: same RBAC ('acknowledge') + CSRF + site
scope as ack. Tagging also acknowledges (an FP is a handled event - leaving
it unacknowledged would keep it alarming). COALESCE keeps the FIRST tagger:
a second tag never rewrites who made the original audit-relevant call.
- move_events.false_positive_by/at (migration included), audit-logged.
- GET /api/fp-stats?days=N: per-(camera, event_type) totals + FP counts,
FP>0 groups only, fp-desc, fail-closed site scoping.
- Console: each open row gets a visually-secondary 오탐 button beside 확인
(can't be fat-fingered as the default); resolved rows show a mono verdict
("오탐 (user)" struck through vs "확인됨 (user)"). New rail panel "오탐율 ·
30일" lists top offenders - 30%+ highlighted as re-tuning candidates -
refreshed on a slow 60s cadence plus immediately after a tag. Detail view
shows the tag.
Verified: PHPUnit 135 pass / pytest unchanged + Chrome real-render (tag ->
row flips to struck-through verdict + drops out of unacked KPI/tree counts ->
FP panel updates immediately; no console errors).