Add canonical tables, cohorts, vendor datasheet and manifest

cohorts/all/embeddings.parquet

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cohorts/all/labels.parquet

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cohorts/all/predictions.parquet

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cohorts/site_retrospective/embeddings.parquet

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cohorts/site_retrospective/features.parquet

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cohorts/site_retrospective/labels.parquet

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cohorts/site_retrospective/predictions.parquet

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cohorts/vendor_train/embeddings.parquet

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cohorts/vendor_train/features.parquet

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cohorts/vendor_train/labels.parquet

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cohorts/vendor_train/predictions.parquet

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manifest.json

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+  "source": "TotalSegmentator v2.0.1",
+  "pool_scans": 567,
+  "eligible": 555,
+  "vendor_train": 333,
+  "site_retrospective": 222,
+  "aaa": {
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+    "site_retrospective": 24
+  },
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+    "vendor_datasheet/aaa-baseline-v0.json": "7ac2b5cec0115df2305dc25014889f1236fefeeedd29efb70687a114bd7b10e1"
+  }
+}

tables/cases.parquet

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tables/pipeline/embeddings.parquet

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tables/pipeline/features.parquet

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tables/pipeline/score.parquet

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vendor_datasheet/aaa-baseline-v0.json

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+{
+  "schema": "slicepoint/vendor-datasheet/0-draft",
+  "model": {
+    "name": "AAA baseline v0",
+    "task": "abdominal aortic aneurysm detection on CT",
+    "rule": "infrarenal max outer-wall diameter (centerline-orthogonal) >= 30 mm on the TotalSegmentator aorta mask"
+  },
+  "training_data": {
+    "n_scans": 333,
+    "n_patients": 333,
+    "source": "TotalSegmentator v2.0.1 (University Hospital Basel), vendor_train split",
+    "age_years": {
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+      "iqr": [
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+      "min": 19.0,
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+    "sex": {
+      "F": 0.4264,
+      "M": 0.5736
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+    "scanner_vendor": {
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+      "philips": 0.0871,
+      "siemens": 0.8589,
+      "unknown": 0.009
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+    "contrast_phase": {
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+      "non-contrast": 0.1862,
+      "venous": 0.5976
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+    "slice_thickness_class": {
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+      "thick": 0.1441,
+      "thin": 0.5465
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+    "max_aortic_diameter_mm": {
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+  },
+  "not_disclosed": [
+    "individual cases",
+    "joint distributions",
+    "embeddings",
+    "protocol names"
+  ]
+}