Add causal oracle person information screen

docs/easycom_track_gru_residual.md

@@ -62,8 +62,14 @@ re-extraction.
 
 Runtime status (2026-09-07): the focused causal-history, exact-zero-gate and
 train/infer round-trip tests passed in 49.699 seconds on the remote PyTorch/L20
-environment. This verifies the code path, not model quality. The one-session
-GPU training smoke and full experiment remain unmeasured.
+environment. The subsequent matched four-epoch screen produced no meaningful
+change: Session-12 three-seed mean-mAP delta was `+0.01306 +/- 0.02368`
+percentage points, and the seed-0 Sessions-1--3 delta was `-0.00030` points.
+The selected residual gates remained between `-0.0015` and `+0.0108`. Because
+the zero scalar gate blocks the track branch's gradient at initialization, this
+run is classified as an optimization failure, not a clean negative result for
+track continuity. Exact values and caveats are archived in
+[`../results/easycom_track_gru_residual_4ep_2026-09-07/README.md`](../results/easycom_track_gru_residual_4ep_2026-09-07/README.md).
 
 ## Fair initialization
 
@@ -73,6 +79,14 @@ feature contract before copying the pooled path. By default those copied
 parameters are frozen. The residual gate starts at zero, so before optimization
 the track model must reproduce the pooled logits exactly, element for element.
 
+The measured screen exposed a defect in that parameterization. At a zero gate,
+the first-step gradient of every residual-branch parameter is also zero; only
+the scalar gate can move, and later branch gradients remain multiplied by its
+small value. A corrected follow-up should instead zero-initialize the final
+residual output layer and remove the scalar multiplier. That preserves exact
+pooled logits at initialization while allowing the output layer to receive a
+gradient immediately.
+
 The matched screening protocol is:
 
 - EasyCom Session 4--11: training;