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RELEASE_NOTES.md

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+# Version 1.0.0
+
+This is the frozen manuscript-model release for the one-pass 3 by 3 median-filter analysis.
+
+Included models:
+
+- 12-offset aggressive-acceleration RFR;
+- 20-offset primary RFR.
+
+The release does not include participant imaging, liver ROIs, voxel-level labels, exploratory comparator models, or earlier training runs. Exact offsets, preprocessing, estimator settings, and file hashes are recorded in `model_manifest.json`.
+
+Developed by Vadim Malis, 2026, University of California San Diego.

SHA256SUMS.txt

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+1eae5b4992c467e746793391f9c0ee753d1bbf1a94396767ff0f4393f9aec26a  models/liver_zap_rfr_12_offsets.joblib
+12674f4f29702739ecb63cc0dbef9e20c46f461f63a17bd177dd0ed37a1ce13d  models/liver_zap_rfr_20_offsets.joblib

environment.txt

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+numpy==2.5.2
+scipy==1.18.1
+scikit-learn==1.9.0
+joblib==1.5.3

model_manifest.json

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+{
+  "release": "1.0.0",
+  "description": "Frozen liver ZAP RFR manuscript models",
+  "author": "Vadim Malis",
+  "affiliation": "University of California San Diego",
+  "input_processing": "one in-plane 3 by 3 median-filter pass per offset",
+  "normalization": "mean measured signal at negative and positive far-offset anchors",
+  "targets": [
+    "fraction_free",
+    "t2_free_us",
+    "t2_restricted_us"
+  ],
+  "target_transform": [
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+    "log10",
+    "log10"
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+  "feature_mode": "physics_spectral",
+  "estimator": {
+    "separate_forests": 3,
+    "n_estimators_per_target": 300,
+    "max_depth": 24,
+    "min_samples_leaf": 2,
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+  "selection": {
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+}

zap_rfr_models_v1.zip

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