Data Dictionary
Training data
| File | Unit of observation | Required keys | Description |
|---|---|---|---|
data/proteins.parquet |
protein sequence | protein_id, sequence_sha256 |
Unique amino-acid sequence records and sequence lengths. |
data/training_units.parquet |
protein-stage assignment | protein_id, sequence_sha256 |
Indicates whether a protein participates in base training, region refinement, or both. |
data/base_training_schedule.parquet |
scheduled training draw | protein_id, sequence_sha256, update, rank, slot |
Deterministic base-training ordering, sampling tier, source, and label metadata. |
data/region_supervision.parquet |
region-supervision record | protein_id, sequence_sha256, supervision_id |
Final DPR region targets, evidence provenance, loss permissions, and region boundaries. |
Join all training tables to data/proteins.parquet on both protein_id and sequence_sha256. In region_supervision.parquet, region_start and region_end are sequence-index boundaries; consult the published PhaseFlow workflow before converting them to model tensors.
Evaluation benchmark
benchmark/ is evaluation-only and is documented in ../benchmark/README.md. The benchmark’s proteins.csv has no protein_id overlap with data/training_units.parquet. Never include benchmark files in a sampler or use them for model selection.
Configuration and integrity metadata
configs/dataset_contract.yaml defines the package contract and configs/training.yaml records public training settings. metadata/feature_reproduction.md describes feature reconstruction boundaries. metadata/file_inventory.csv lists every package file other than itself with its byte size and SHA-256 digest.