Datasets

Bar datasets

Built by research/dataset.py + model_generation/ with quality gates

(coverage, ordering, duplicates, horizon boundaries). Each dataset is a

versioned artifact with a fingerprint (ds_* id) used in manifests and run

snapshots.

Tick datasets (CHG-0041 / TICK_DATASET_META v2)

research/mt5_tick_dataset.py acquires ticks from the **certified adapter

surface** (copy_ticks_range, COPY_TICKS_ALL), with:

• bounded, deduplicated acquisition (post BUG-188 semantics),
• immutable parquet store with content fingerprints,
• provenance metadata v2 (symbol, window, source, acquisition identity),
• cache-hit idempotence — re-running acquisition never duplicates.

After acquisition the dataset is fully offline: research needs no broker.

Rules

1. A dataset is immutable once fingerprinted — corrections produce a new

dataset, never a mutation.

1. Every experiment names its dataset ID; manifests and run snapshots carry it.
2. Dataset-fairness: A/B/C model comparisons must consume equal data windows,

seeds and splits (the TASK-04 protocol).

1. Provenance fields may be NOT_RECORDED (honest) — they are never invented.