integ: land 2 clean backlog branches#69
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…harness refs) The neural-fabric CI gate referenced files that were never committed anywhere: schemas/neural-fabric/intervention-event.v1.json (in neural-fabric-static) and the whole neural-fabric-smoke harness (scripts/validate-neural-fabric-results.py, scripts/check-capacity-bounds.py, tests/neural_fabric). This module delivers the 3 JSON schemas + the neural_fabric package (hopfield/may_wigner); the validation/ experiment harness is not yet built. Drop the dangling intervention-event schema line, and make neural-fabric-ci gate only neural-fabric-static (schema validation + package compile). smoke/full targets are kept as the roadmap for the harness and excluded from CI until those files land. neural-fabric-ci green.
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PR #69 scoped neural-fabric-ci to neural-fabric-static because the smoke/full targets referenced files that were never committed. This builds that harness against the actual reference primitives (may_wigner + hopfield): - scripts/check-capacity-bounds.py — May-Wigner capacity gate (--m/--C/--s -> s*sqrt(m*C), classify, exit non-zero past the allowed ceiling). - scripts/validate-neural-fabric-results.py — jsonschema conformance for families/experiments/results/events + the doctrine invariant (weights_updated is always false) + result/event -> experiment cross-references. - research/activation-time-targeting/code/run_suite.py — deterministic CPU-only suite: NF-ATT-001 (Hopfield logit-boost steering, no weight update) and NF-ATT-002 (May-Wigner capacity sweep). Emits targeting-result.v1 docs and, for interventions, intervention-event.v1 audit records. - tests/neural_fabric/ — known-answer tests for the primitives + invariants on the committed reference artifacts (25 tests). - schemas/neural-fabric/intervention-event.v1.json — restores the intended audit-event schema dropped in #69 (interventions are governed by audit events). - Committed reference family/experiments/results/events under research/activation-time-targeting/. mk: re-add intervention-event to neural-fabric-static and neural-fabric-smoke to neural-fabric-ci; neural-fabric-full now regenerates the reference artifacts in place (reproducibility check). Workflow installs jsonschema. Verified: make -f mk/neural-fabric.mk neural-fabric-ci green (8 artifacts valid, capacity PASS, 25 tests); full repo pytest 92 passed; ruff clean.
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Phase 1 integration — clean-mergeable backlog (real content, no conflict vs main): capture/spo-baez-algebra-engine neural-fabric-capture. CI-gated.