analysis: identify hierarchical spatial credit bottleneck

1 files changed, 9 insertions, 0 deletions

diff --git a/ROADMAP.md b/ROADMAP.md
index 4f6c315..15699e2 100644
--- a/ROADMAP.md
+++ b/ROADMAP.md
@@ -383,6 +383,15 @@ 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.
 
+The fixed post-failure hierarchical oracle identifies the substantive next
+change. Ordinary downstream activation context moves early alignment only from
+`0.031123` to `0.032069`, while held-out local maps from the actual residual-DAG
+child error fields reach `0.440525` (1x1), `0.819917` (3x3), and `0.999767`
+(3x3 plus the locally available child ReLU gate). This is not task evidence
+and uses exact child gradients as oracle inputs. It establishes that future
+development should learn spatial hierarchical feedback without weight copying,
+with random/fixed hierarchical FA and BurstCCN as mandatory baselines.
+
 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