Add EgoSpeak dense event proxy evaluation

docs/README.md

@@ -34,7 +34,8 @@ tests.
 | [`easycom_competing_risk_floor_evaluation.md`](easycom_competing_risk_floor_evaluation.md) | Running and auditing the competing-risk entry/yield evaluator with training-side threshold calibration |
 | [`easycom_floor_event_diagnostics.md`](easycom_floor_event_diagnostics.md) | Separating boundary observability, event-objective mismatch and addressee information with remote commands |
 | [`easycom_event_review_tool.md`](easycom_event_review_tool.md) | Reviewing automatically mined EasyCom floor-event candidates against local video and transcripts |
-| [`easycom_annotated_floor_evaluation.md`](easycom_annotated_floor_evaluation.md) | Scoring human-confirmed point events and hard-negative opportunity regions at fixed EgoSpeak horizons |
+| [`easycom_egospeak_event_proxy.md`](easycom_egospeak_event_proxy.md) | Scoring the EgoSpeak wearer trajectory over equal-width causal decision regions as an activity-derived ENTRY/INT proxy |
+| [`easycom_annotated_floor_evaluation.md`](easycom_annotated_floor_evaluation.md) | Reproducing the legacy asymmetric point-positive/region-negative fixed-horizon diagnostic |
 
 ## Design history and implementation options
 

docs/easycom_annotated_floor_evaluation.md

@@ -1,4 +1,10 @@
-# EasyCom human-annotated fixed-horizon floor-event evaluation
+# Legacy EasyCom fixed-horizon floor-event diagnostic
+
+> **Status:** retained for reproducibility, not the current manuscript event
+> protocol. Its one-bin positives and variable-duration hard-negative regions
+> are asymmetric. Use the equal-width activity-derived protocol in
+> [`easycom_egospeak_event_proxy.md`](easycom_egospeak_event_proxy.md) for the
+> current EgoSpeak baseline.
 
 This protocol evaluates saved EgoSpeak-layout dense predictions against
 human-confirmed `WEARER_ENTRY`, `INT_YIELD`, and hard-negative opportunities.

docs/easycom_egospeak_event_proxy.md

@@ -0,0 +1,48 @@
+# EgoSpeak dense-trajectory event proxy
+
+`evaluate_egospeak_event_proxy.py` provides a deliberately limited bridge
+between EgoSpeak-compatible dense future-activity predictions and reviewed
+wearer ENTRY/INT opportunities. It does **not** claim that wearer voice
+activity is a semantic floor-event detector.
+
+## Score
+
+For every positive event, the default decision region contains the three 5-Hz
+source rows immediately before its corrected behavior anchor. An independently
+mined hard negative uses the first three rows of its labeled opportunity. A raw
+wearer onset/offset relabeled as a hard negative uses the same pre-boundary
+region as a positive. Regions shorter than 0.6 seconds are excluded and
+counted; longer annotation evidence is not scored.
+
+At each source row, the script recovers the target-aligned wearer trajectory
+at 0.6, 0.8, ..., 2.0 seconds. ENTRY uses its mean and INT uses one minus its
+mean. Max-pooling over the three decision rows produces one score per reviewed
+opportunity. The output must be called an `activity-derived event proxy`.
+
+## Threshold-free provisional run
+
+This reports AP without fitting thresholds on Sessions 1--3:
+
+```bash
+python3 evaluate_egospeak_event_proxy.py \
+  --reviews reports/easycom_entry_int_sessions1_4_v16/easycom_eot_int_provisional_llm_reviews.jsonl \
+  --run egospeak=results/egospeak_miniroada_floor_eval \
+  --sessions Session_1 Session_2 Session_3 \
+  --allow-provisional-llm-reviews \
+  --print-event-examples 5 \
+  --output results/easycom_egospeak_event_proxy/sessions1_3_provisional_summary.json
+```
+
+The command writes JSON, a compact metrics CSV, and an event CSV containing the
+three decision-frame scores and the winning selected-horizon wearer trajectory.
+
+## Recall-matched operating points
+
+`--matched-recalls` on official test sessions additionally requires disjoint
+Sessions 4--12 reviews and predictions via `--calibration-reviews`,
+`--calibration-sessions`, and optionally `--calibration-run`. Do not use
+`--allow-in-sample-thresholds` for reported results.
+
+The default 0.6-second decision window and 0.6--2.0-second trajectory range
+remain protocol choices to freeze using training-side data. Report shorter or
+longer windows only as predeclared sensitivity analyses.