NFC Falsification Criteria

NFC must be allowed to fail. These criteria block model-superiority language.

• Old 5-step NFC synthetic signals produced before the corrected gate are invalidated as evidence. They may be kept only as debugging history.

• If NFC cannot beat direct baselines on synthetic latent-field recovery, stop before A100.

• If no-pair NFC equals full NFC, the pair kernel is decorative.

• If observation-operator-free NFC equals full NFC, compiler factorization is decorative.

• If uncertainty does not correlate with error, confidence maps are decorative.

• If any task pads, broadcasts, or silently reshapes predictions to hide shape mismatch, the gate fails.

• If an autoregressive or retrieval baseline uses held-out test targets, the gate fails.

• If required metrics, ablation rows, or finite uncertainty diagnostics are missing, the gate fails.

• If ridge beats NFC on all real fMRI tasks, make no model-superiority claim.

• If real stimulus hash is not verified, make no stimulus-to-fMRI claim.

• If Brain-OF-style or exact Brain-OF matches NFC on leakage-proof translation and adaptation tasks, do not claim a generic multimodal advantage.

Synthetic and debug results are plumbing evidence only.

The next A100 step is strict 1x NFC synthetic diagnostic only:

PYTHONPATH=src python3 -m neurotwin.cli eval \
  --suite nfc_synthetic \
  --out-dir "$RUN_ROOT" \
  --train-steps 50 \
  --seeds 0 1 2 \
  --require-pass