AGENTS.md

Working with agents: OLIVE FRP dataset

Orientation for an AI agent using this HuggingFace dataset (ApocalyVec/olive-physio). See README.md (the dataset card) for full field docs.

Load it

from datasets import load_dataset
frp = load_dataset("ApocalyVec/olive-physio", "default")   # fixation-locked FRP epochs
ern = load_dataset("ApocalyVec/olive-physio", "ern")       # response-locked ERN epochs

Two configs: default (data/frp_dataset.parquet) and ern (data/ern.parquet).

Conventions an agent MUST respect

• y == 1 is the target, y == 0 non-target (default config). Targets are the minority class (~40%). Do not assume 1=non-target.
• task is a per-EPOCH label (visual_search = calibration blocks, spaceshooter = gameplay blocks). Both occur within every study session; it is not a per-study field. Filter by task, not by user_study, to separate the two tasks.
• p_target (default config) is a per-fixation implicit-evidence probability for auditability / decoder-swap comparison; it is present for US2/US3 only (NaN for US1) and is not the literal value used in the studies.
• condition (IE/E) is the as-published label; use it for anything that should agree with the paper. condition_ra is an unresolved audit overlay; ignore it for paper-facing work.
• ERN config: label is 0=correct (enemy hit) / 1=error (friendly fire); epochs are response-locked [-200, 600] ms @256 Hz ([20, 205]), 0.5 to 30 Hz filtered.
• eeg loads as a nested array; reshape a row via np.array(row.tolist(), dtype=np.float32) → [20, 230] (default) / [20, 205] (ern). EEG is 256 Hz; FRP window is [-0.1, 0.8] s.
• saccade_* / fixation_duration are NaN by default (a separate opt-in derivation).

Cohort & provenance

25 subjects (the OLIVE IE+E cohort with data). The paper describes the studies and the implicit-evidence channel; this card does not duplicate that. Code + reproduction: https://github.com/ApocalyVec/olive