results: close Oral-A v3 causal-capture gate

1 files changed, 10 insertions, 0 deletions

diff --git a/ROADMAP.md b/ROADMAP.md
index 2ad919f..4f6c315 100644
--- a/ROADMAP.md
+++ b/ROADMAP.md
@@ -373,6 +373,16 @@ reaches `0.00721`. Naive local-average/channel-context fields fall slightly to
 sample efficiency and feedback context; simply lowering `eta_A`, adding the
 tested fields, or reopening V2-2 is not justified.
 
+**Vectorizer-space V3 status: causal-capture gate failed.** Directly estimating
+the A/G matrix target passed exact mechanics and reduced matched synthetic
+one-query MSE to `0.03381x`, but its selected real early alignment was
+`0.007139` versus the matched V2 reference's `0.007209`. All-layer alignment
+rose from `0.052740` to `0.062579`; three early/oracle checks failed and only
+the all-layer check passed. V3 full training was not launched, and test access
+remains sealed. This closes learning-rate tuning of the same output-error-only
+channel-gated family; a further branch must make a substantive feedback-context
+or cross-layer-noise change.
+
 Prepare convolutional local-update primitives and ResNet-20/32/56 protocols early. Queue frozen
 runs opportunistically on authorized idle GPUs. Because BurstCCN already reports CIFAR-10 and
 ImageNet scaling, dataset scale alone is not novel. The oral-level target is a memorable joint