Fix opportunity competing-risk evaluation

docs/easycom_opportunity_event_evaluation.md

@@ -10,6 +10,12 @@ head.
 
 A positive must have a reviewer-selected preceding non-wearer release. Its
 opportunity starts at that release and resolves at the reviewed wearer entry.
+If a new non-wearer onset occurs before or exactly at that entry, the release
+has already been resolved by a competing event and the positive is excluded.
+The same applies when wearer activity already occurred between the selected
+release and the reviewed onset: the selected release is then a stale,
+post-outcome anchor. Both cases are counted separately in
+`review_diagnostics.skipped`.
 Core hard negatives start at the same type of non-wearer release and resolve
 when the same speaker resumes (`ENTRY_OTHER_MIDTURN_PAUSE`) or a different
 non-wearer takes the next floor (`ENTRY_OTHER_TO_OTHER`). The score is the
@@ -27,10 +33,10 @@ the maximum `1 - p_wearer` over 0.2--0.6 seconds, censored strictly at that
 non-wearer's offset. Reviewed `INT_YIELD` items are positive; other
 backchannels, failed takeovers, and clear wearer-hold cases are hard negatives.
 
-Current INT reviews do not select one competing onset. The loader therefore
-uses the latest supplied other interval that crosses the wearer offset within
-the annotation tolerance. It records how many intervals were eligible so
-multi-competitor cases can be audited before the protocol is frozen.
+Current INT reviews do not select one competing onset. A unique supplied other
+interval that crosses the wearer offset within the annotation tolerance is
+used. Cases with multiple eligible intervals are excluded and counted rather
+than being assigned a deterministic latest-onset anchor.
 
 ## Provisional EgoSpeak run
 
@@ -58,21 +64,24 @@ Before manuscript reporting, freeze the 2.0-second ENTRY cap, 0.6-second YIELD
 cap, positive anchor-selection policy, and multiple-competitor handling using
 training-side data only.
 
-## Recorded Sessions 1--3 baseline
+## Superseded v1 Sessions 1--3 baseline
 
-The first threshold-free run gives ENTRY AP 52.487% (163 positive, 335 hard
-negative; 32.731% prevalence) and INT/YIELD AP 20.135% (28 positive, 109 hard
-negative; 20.438% prevalence). It excludes 81 ENTRY and 5 INT cases as invalid
-or post-outcome. These are provisional LLM-assisted labels, not human-reviewed
-confirmatory results. Dense, raw-boundary, and opportunity metrics and their
-Figure 7 interpretation are frozen together in the
+The first threshold-free run used the superseded v1 loader and reported ENTRY
+AP 52.487% (163 positive, 335 hard negative; 32.731% prevalence) and INT/YIELD
+AP 20.135% (28 positive, 109 hard negative; 20.438% prevalence). It excluded
+81 ENTRY and 5 INT cases as invalid or post-outcome. These opportunity values
+must not be reported: v1 allowed a
+selected ENTRY release to cross an intervening other onset and selected the
+latest onset in ambiguous multi-competitor INT cases. Dense and raw-boundary
+metrics are unaffected. Rerun the opportunity evaluation with protocol v2
+before updating the manuscript. The historical output is retained in the
 [`2026-09-16 result record`](../results/easycom_egospeak_three_level_eval_2026-09-16/README.md).
 
-The expanded Omni screen finds no opportunity-ranking gain from the current
+The expanded v1 Omni screen found no opportunity-ranking gain from the current
 F1 Frame-set Attention model: its three-seed ENTRY/INT AP is
 41.561%/22.991%, below the historical pooled-V seed-0 values
 46.022%/24.266%. Because F1 and that pooled run use different train/dev model-
-selection protocols, this is a stable negative screen rather than a matched
-confirmatory comparison. Dense, boundary, per-seed, and provenance details are
+selection protocols and used the superseded opportunity loader, only its dense
+and raw-boundary findings remain current. Per-seed and provenance details are
 in the
 [`Omni floor screening record`](../results/easycom_omni_floor_screen_2026-09-16/README.md).

docs/omni_speaker_floor_experiment_plan_2026-08-30.md

@@ -168,12 +168,13 @@ forecasting 的定性解释，不能代替 boundary 或 semantic opportunity 评
 曲线和限制见
 [`three-level baseline record`](../results/easycom_egospeak_three_level_eval_2026-09-16/README.md)。
 
-当前 F1 current-frame person-set screen 的三种子结果同样没有支持 semantic floor
-selectivity：ENTRY/INT opportunity AP 为 `41.561 +/- 0.581` / `22.991 +/- 0.202`，
-低于历史 pooled-V seed-0 的 `46.022/24.266`；dense mean mAP 也为
-`64.951 +/- 0.095`，没有超过历史 pooled-V 的 `65.400`。由于两者 train/dev
-选择协议不同，这只能判为稳定的负向 screening，正式归因前必须补同协议三种子 pooled
-control。详见 [`Omni floor screening record`](../results/easycom_omni_floor_screen_2026-09-16/README.md)。
+当前 F1 current-frame person-set screen 的 dense mean mAP 为
+`64.951 +/- 0.095`，没有超过历史 pooled-V 的 `65.400`。原 v1 evaluator 给出的
+ENTRY/INT opportunity AP（`41.561 +/- 0.581` / `22.991 +/- 0.202`）已失效：v1
+可能跨过 competing ENTRY onset，且会在多个 INT competitor 中任意选择 latest onset。
+必须用 v2 重跑后才能判断 semantic floor selectivity；正式归因还必须补同协议三种子
+pooled control。历史数值与勘误见
+[`Omni floor screening record`](../results/easycom_omni_floor_screen_2026-09-16/README.md)。
 
 ### P3：第一优先方法——匿名逐人时序旁路