{ "meta_info": { "case_id": "case21_02", "bench_subset": "NeuroBench-Multi", "difficult": 2, "original_dataset": "simultaneous" }, "agent_input": { "data_path": [ "data/multi/simultaneous_01_run-gonogo1_EEG.edf", "data/multi/simultaneous_01_run-gonogo1_fNIRS.edf" ], "instruction": "Analyze EEG–fNIRS temporal correspondence during `[94, 184)` seconds using 5-second windows stepped every 5 seconds.\n\nFor each window, summarize beta-band activity in `[13, 30)` Hz across EEG channels `FP1`, `AFz`, `F1`, `C3`, `Cz`, `Pz`, `O1`, and `O2`. Derive the HbO trajectory from fNIRS pair `S03D02` using the public fNIRS conversion procedure.\n\nCompute the Pearson correlation between the EEG and HbO trajectories at zero lag and with HbO delayed by 5 seconds.\n\nReport only `zero_lag_correlation` and `delayed_correlation`." }, "eval_config": { "parser_prompt": "### ROLE\nYou are a precise JSON extraction engine for an EEG--fNIRS window-correlation task.\n\n### TASK\nExtract the two final Pearson correlations from the agent's report.\n\n### REQUIRED FIELDS\n- `zero_lag_correlation`: a finite Pearson correlation in `[-1, 1]`, or `null`\n- `delayed_correlation`: a finite Pearson correlation in `[-1, 1]`, or `null`\n\n### STRICT CONSTRAINTS\n1. Output only one valid JSON object.\n2. Use exactly the two required keys.\n3. Do not include Markdown, explanations, units, window values, or extra fields.\n4. Do not calculate or infer a missing value.\n5. Preserve the numeric field names exactly.\n\n### OUTPUT TEMPLATE\n{\"zero_lag_correlation\": , \"delayed_correlation\": }", "metrics": [ { "metric_id": "zero_lag_correlation", "type": "numeric_check", "target_key": "zero_lag_correlation", "weight": 50, "params": { "gt_value": -0.660369718678305, "tolerance": 0.0660369718678305 } }, { "metric_id": "delayed_correlation", "type": "numeric_check", "target_key": "delayed_correlation", "weight": 50, "params": { "gt_value": -0.5741777584765132, "tolerance": 0.05741777584765132 } } ] } }