feat(api): GET /experiments/runs + POST /experiments/diff (Track 5)

feat(api): POST /explain/eeg + /explain/mri — full-stack Track-1 coverage

feat(llm): modality dispatch — explain(payload, modality) for BBB/EEG/MRI

feat(api): POST /explain/bbb — natural-language rationale endpoint

feat(llm): explainer with deterministic template + OpenRouter fallback

feat(api+frontend): MLflow provenance badge in decision card

feat(api): drift z-score in /predict/bbb response

feat(models): train-time confidence stats stashed on _neurobridge_train_stats

feat(api): POST /pipeline/mri/diagnostics — pre/post ComBat KPIs + long-format rows

feat(pipelines): compute_harmonization_diagnostics — long-format pre/post ComBat for viz

feat(api): expose calibration bin in /predict/bbb response

feat(models): calibration metadata — precision-at-threshold bins on _neurobridge_calibration

feat(api): POST /predict/bbb with prediction, uncertainty, SHAP top-k

feat(models): SHAP top-k explainer for BBB predictions

feat(models): BBB classifier with predict_with_proba uncertainty

feat(frontend): Streamlit dashboard with 3 modality tabs

feat(api): POST /pipeline/{bbb,eeg,mri} dispatch routes

feat(api): scaffold FastAPI app + /health + shared Pydantic schemas

feat(mri): log run params, metrics, and parquet artifact to MLflow

feat(eeg): log run params, metrics, and parquet artifact to MLflow

feat(bbb): log run params, metrics, and parquet artifact to MLflow

feat(core): add MLflow tracking helper with disable env-flag

test: cross-pipeline smoke run for all three modalities

feat(core): extract write_parquet() helper for §6 storage contract

feat(core): extract pin_threads() helper for determinism

fix(mri): handle all-constant features; tighten variance threshold; reorder log

feat(mri): add run_pipeline orchestrator + CLI (NIfTI dir → ComBat Parquet)

fix(mri): pin ComBat transitive deps; clarify np.round(14) intent; guard inputs

feat(mri): add harmonize_combat wrapper around neuroHarmonize.harmonizationLearn

refactor(mri): bind ROI_STATS to callables; guard volume/mask shape mismatch

feat(mri): add extract_features_from_volume (8 ROI octants × 6 stats)

fix(mri): warn on all-False mask; document 6-connectivity erosion caveat

feat(mri): add mask_brain (intensity threshold + morphological opening)

feat(mri): add is_valid_volume guard for NaN/inf/shape/dtype on 3-D arrays

docs(mri): add build() docstring; fail-fast on unknown site label

test(mri): add deterministic synthetic NIfTI fixture (6 subjects × 2 sites)

docs(eeg): correct float64 dtype claim; tighten test match; clarify CLI default

feat(eeg): add run_pipeline orchestrator + CLI (FIF/EDF → Parquet)

fix(eeg): NaN-clean features for flat channels; guard zero-size epochs; assert WARNING

fix(eeg): validate epochs after filter to guarantee no NaN in feature table

feat(eeg): flatten 3D epochs into deterministic 2D feat_<ch>_<band|stat> table

refactor(eeg): bind STATS labels to callables; document moment conventions

feat(eeg): add compute_features_from_epoch (PSD bands + 5 statistics)

refactor(eeg): tighten ICA docstring + log accuracy; extract EOG threshold constant

feat(eeg): add remove_artifacts_with_ica with EOG correlation rejection

fix(eeg): guard bandpass_filter against inverted l_freq/h_freq; document picks=all

feat(eeg): add non-mutating bandpass_filter (default 1-40 Hz)

fix(eeg): tighten is_valid_epoch signature; reject non-numeric dtype + -inf

feat(eeg): add is_valid_epoch guard for NaN/inf/shape/dtype

docs(eeg): note MNE-pin coupling for fixture determinism