Add/update downstream bootstrap reference: README.md

downstream/bootstrap/README.md

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+# Downstream bootstrap reference
+
+This subdir holds the **Phase-1 bootstrap reference** for the Track-1 (outcome
+prediction) leaderboard recompute — the long-format per-draw error frame that the
+skill / rank / fairness CIs reduce from.
+
+## Layout
+
+```
+downstream/bootstrap/
+├── draws.parquet      # per-(method, task, subgroup, draw) error E = 1 − metric
+└── draws.meta.json    # provenance: seed, n_boot, methods, n_tasks, fairness attrs
+```
+
+## What's it for
+
+Each row of `draws.parquet` is one bootstrap draw of one task for one method,
+carrying the per-draw error `E = 1 − metric` (binary AUPRC, ordinal Spearman,
+regression Pearson). Phase-2 reduces the same frame three ways, all paired vs the
+`linear` baseline:
+
+- **Skill score** `S = 1 − geomean_task(E_method / E_linear)` — domain-balanced
+  macro; per-(method, scope) mean / SE / percentile-CI across draws.
+- **Average rank** — per-(method, scope) mean of the per-draw cross-method rank
+  (lower `E` → rank 1).
+- **Fairness skill score** — per-attribute disparity ratio over the `age_group` /
+  `sex` subgroup rows, with BCa intervals.
+
+The per-method `downstream/<method>.parquet` substrate (the raw user pairs, one level
+up) is the *input* the draws were bootstrapped from; this frame is the precomputed
+result so consumers need not re-run the 1000-draw paired bootstrap.
+
+## Provenance
+
+Generated by `scripts/paper_results/downstream/bootstrap_downstream_draws.py` in the
+code repo. The current snapshot was built with:
+
+- `seed = 42`, `n_boot = 1000`
+- `split = test`, canonical `sharable_users_seed42_2026`
+- 8 methods (see `draws.meta.json:methods`), 32 tasks, baseline `linear`
+- fairness attributes `age_group`, `sex`
+
+Parity of this frame against the uploaded per-method substrate is enforced by
+`scripts/paper_results/downstream/parity/parity_substrate.py` (a substrate-driven
+bootstrap must reproduce these draws).
+
+## Loading
+
+```python
+from huggingface_hub import hf_hub_download
+import pandas as pd, json
+
+draws_path = hf_hub_download(
+    "MyHeartCounts/OpenMHC-leaderboard-data",
+    "downstream/bootstrap/draws.parquet",
+    repo_type="dataset",
+)
+meta_path = hf_hub_download(
+    "MyHeartCounts/OpenMHC-leaderboard-data",
+    "downstream/bootstrap/draws.meta.json",
+    repo_type="dataset",
+)
+draws = pd.read_parquet(draws_path)
+meta = json.loads(open(meta_path).read())
+print(meta["seed"], meta["n_boot"], len(meta["methods"]))
+```
+
+See [`SCHEMA.md`](SCHEMA.md) for the full column spec.
+
+## Uploaded with
+
+`tools/upload_leaderboard_bootstrap.py --track downstream` in the
+[code repo](https://github.com/AshleyLab/myheartcounts-dataset).