From 5dcd29000579d9dea626b47f84aa3fdc16700605 Mon Sep 17 00:00:00 2001
From: YurenHao0426 <Blackhao0426@gmail.com>
Date: Wed, 22 Jul 2026 12:41:18 -0500
Subject: results: close Oral-A v2 causal-capture gate

---
 experiments/analyze_oral_a_failure.py | 44 ++++++++++++++++++++++++++++-------
 1 file changed, 35 insertions(+), 9 deletions(-)

(limited to 'experiments')

diff --git a/experiments/analyze_oral_a_failure.py b/experiments/analyze_oral_a_failure.py
index 9f84bbf..bf68d12 100644
--- a/experiments/analyze_oral_a_failure.py
+++ b/experiments/analyze_oral_a_failure.py
@@ -23,6 +23,8 @@ def main():
         "--short", default="results/oral_a_short/sdil_channel_gated_lr0.03.json")
     parser.add_argument(
         "--gate", default="results/oral_a_full_gate.json")
+    parser.add_argument(
+        "--v2_gate", default="results/oral_a_v2_calibration_gate.json")
     parser.add_argument(
         "--out", default="results/oral_a_failure_diagnosis.json")
     args = parser.parse_args()
@@ -30,6 +32,7 @@ def main():
     full = load(args.full)
     short = load(args.short)
     gate = load(args.gate)
+    v2_gate = load(args.v2_gate)
     expected = {
         "mode": "sdil", "depth": 20, "epochs": 200,
         "vectorizer_mode": "channel_gated", "a_scale": 1.0,
@@ -42,6 +45,9 @@ def main():
         raise ValueError("full A3 result has tracked source edits")
     if gate["status"] != "failed" or gate["confirmation_test_seeds_touched"]:
         raise ValueError("expected a failed A3 gate with untouched confirmation")
+    if (v2_gate["status"] != "failed"
+            or v2_gate["confirmation_test_seeds_touched"]):
+        raise ValueError("expected a failed v2 gate with untouched confirmation")
 
     calibration_rows = []
     first_nonfinite_epoch = None
@@ -82,9 +88,14 @@ def main():
     max_mse_power_gap = max(abs(row["mse_to_target_power"] - 1.0)
                             for row in calibration_rows)
     short_calibration = short["apical_warmup"]["last"]
+    unit = v2_gate["selected"]["unit_targets"]
+    structured = v2_gate["selected"]["channel_subspace"]
     output = {
-        "protocol": "oral_a_A3_failure_diagnosis_v1",
-        "source_paths": {"full": args.full, "short": args.short, "gate": args.gate},
+        "protocol": "oral_a_A3_failure_diagnosis_v2",
+        "source_paths": {
+            "full": args.full, "short": args.short, "gate": args.gate,
+            "v2_gate": args.v2_gate,
+        },
         "source_commits": {
             "full": full["provenance"]["git_commit"],
             "short": short["provenance"]["git_commit"],
@@ -113,17 +124,32 @@ def main():
             "max_abs_prediction_target_cosine_before_nonfinite": max_abs_cosine,
             "max_abs_mse_to_target_power_minus_one": max_mse_power_gap,
         },
+        "post_failure_v2_refinement": {
+            "unit_target_early_third_alignment": (
+                unit["metrics"]["early_third_alignment"]),
+            "unit_target_all_layer_alignment": (
+                unit["metrics"]["all_layer_alignment"]),
+            "structured_early_third_alignment": (
+                structured["metrics"]["early_third_alignment"]),
+            "structured_all_layer_alignment": (
+                structured["metrics"]["all_layer_alignment"]),
+            "structured_gate_status": v2_gate["status"],
+        },
         "diagnosis": {
-            "classification": "causal_target_not_captured_before_runaway",
+            "classification": "unit_target_regression_snr_inadequate_before_runaway",
             "evidence": [
-                "prediction-target cosine remains effectively zero",
-                "calibration MSE remains indistinguishable from target power",
+                "instantaneous prediction-target cosine remains effectively zero",
+                "calibration MSE remains indistinguishable from stochastic target power",
                 "target power grows by orders of magnitude before nonfiniteness",
-                "short-run teaching alignment therefore cannot be attributed to learned A",
+                "matched frozen-forward unit targets later yield only 0.0011 early-layer alignment",
             ],
-            "next_test": (
-                "reduce estimator variance by perturbing the representable "
-                "channel-gated feedback subspace, not every spatial unit"),
+            "interpretation_limit": (
+                "instantaneous target metrics alone do not prove zero conditional "
+                "learning; structured v2 has low instantaneous cosine yet positive "
+                "exact-gradient alignment"),
+            "next_test_outcome": (
+                "representable-subspace perturbation improved exact alignment but "
+                "failed the frozen early-layer causal-capture gate"),
         },
     }
     os.makedirs(os.path.dirname(os.path.abspath(args.out)), exist_ok=True)
-- 
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