Add imputation/bootstrap/SCHEMA.md
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imputation/bootstrap/SCHEMA.md
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# Imputation bootstrap reference — schema
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The Track-2 bootstrap reference is two files:
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```
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imputation/bootstrap/draws.parquet # ~107 MB zstd
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imputation/bootstrap/draws.meta.json # provenance sidecar
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```
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## `draws.parquet`
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One row per `(method, scenario, split, channel, channel_type,
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subgroup_attr, subgroup_value, draw)`. Approximate size: **11,374,208
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rows** for the canonical 1000-draw / 16-method / 6-scenario / test-split
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run; `~107 MB` compressed (`zstd`).
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| column | type | description |
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|---|---|---|
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| `method` | string (dict) | method identifier (16 values: `locf`, `mean`, `mode`, `linear`, `temporal_mean`, `temporal_mode`, `personalized_mean`, `personalized_mode`, `personalized_temporal_mean`, `brits`, `dlinear`, `dlinear_weekly`, `fedformer`, `timesnet`, `lsm2`, `lsm2_weekly_sparse`) |
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| `scenario` | string (dict) | masking scenario (6): `random_noise`, `temporal_slice`, `signal_slice`, `sleep_gap`, `workout_gap`, `intensity_failure` |
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| `split` | string (dict) | data split — `test` |
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| `channel` | string (dict) | `ch_0`..`ch_18` (19 sensor channels) or `cat_collapsed:sleep` / `cat_collapsed:workouts` (collapsed-binary tasks) |
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| `channel_type` | string (dict) | `continuous` (`ch_0`–`ch_6`), `binary` (`ch_7`–`ch_18`), or `binary_collapsed` (the `cat_collapsed:*` tasks) |
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| `subgroup_attr` | string (dict) | `all` (global cell), `age_group`, or `sex` |
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| `subgroup_value` | string (dict) | `all` for the global cell; otherwise the subgroup level (age bucket, sex value, or `unknown`) |
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| `draw` | int32 | bootstrap-draw index in `[0, n_boot)` |
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| `E` | float32 | absolute error for this draw, user-macro reduced |
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| `R` | float32 | paired ratio vs baseline (`locf`) for this draw, geomean over users; `1.0` exactly for the baseline-vs-self row, `NaN` if undefined |
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| `rank` | float32 | cross-method rank for this draw, averaged over the resampled cohort |
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### Value semantics
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- **`E`** — per-draw user-macro error. Per channel: continuous = per-user MAE, then `nanmean` over resampled users; binary = `1 − AUC` per user, then `nanmean` over users; `binary_collapsed` = per-user `nanmean(1 − AUC)` over the category's channels, then `nanmean` over users.
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- **`R`** — per-draw paired ratio. Per (user, task) the ratio is `clip(E_method / E_baseline, 0.01, 100)`; per draw, `R = exp(nanmean(log(ratio)))` over resampled users. Binary `E` is `ε = 0.005` floored before forming the ratio so perfect-AUC users contribute finite values.
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- **`rank`** — per-draw cross-method rank. Per (user, task) the rank is `rankdata(E_methods, method="average", ascending=True)` (lower E → rank 1); per draw, `rank = nanmean` over resampled users.
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NaN appears where a task is structurally absent (e.g. binary tasks in the
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`EXCLUDE_BINARY_SCENARIOS` set: `sleep_gap`, `workout_gap`,
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`intensity_failure`).
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## `draws.meta.json`
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Side-car metadata, written next to `draws.parquet`. Schema:
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```jsonc
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{
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"n_boot": 1000,
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"seed": 42,
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"splits": ["test"],
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"scenarios": ["intensity_failure", "random_noise", "signal_slice",
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"sleep_gap", "temporal_slice", "workout_gap"],
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"methods": ["mean", "mode", "locf", ...], // 16 entries
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"method_dirs": {"locf": "/path/to/pairs", ...}, // source pair dirs (cluster-local)
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"include_auc": true,
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"include_fairness": true,
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"age_bins": [18, 30, 40, 50, 60],
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"exclude_unknown": false,
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"elapsed_seconds": 3531.6,
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"n_rows": 11374208,
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"git_commit": "06e4cbda...", // code-repo commit at generation
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"timestamp": "2026-06-19T03:24:21.860842Z",
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"argv": [...] // exact invocation
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}
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```
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## Conventions
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- Evaluated against the canonical split `sharable_users_seed42_2026` (`test`).
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- Track-2 baseline for skill / fairness: `locf`.
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- Format: single Parquet, dictionary-encoded categoricals, `float32` errors, `int32` draw index, `zstd` compression.
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- Resamples are paired across methods — same `boot_idx` matrix per split, so `R` and `rank` are valid per-draw comparisons.
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## Tracks
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| dir | track | status |
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|---|---|---|
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| `imputation/bootstrap/` | Track 2 — Imputation (above) | live |
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| `forecasting/bootstrap/` | Track 3 — Forecasting | added later |
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| `downstream/bootstrap/` | Track 1 — Outcome Prediction | added later |
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