Datasets:
| { | |
| "meta_info": { | |
| "case_id": "case13_04", | |
| "bench_subset": "NeuroBench-Multi", | |
| "difficult": 1.5, | |
| "original_dataset": "DEAP" | |
| }, | |
| "agent_input": { | |
| "data_path": "data/multi/DEAP_04.bdf", | |
| "instruction": "Analyze EEG channel `Pz` and PPG channel `Plet` over [1050, 1350).\n\nDivide both streams into aligned, non-overlapping 30-second windows and pair the windows by index.\n\nFor each window, compute `relative_alpha_power` from the EEG signal as alpha power in [8, 13) Hz divided by total power in [0.5, 45) Hz. Compute `rate_mean` from the PPG signal as mean pulse rate estimated from detected pulse cycles.\n\nKeep windows with finite values for both features. If at least 6 valid pairs remain and both feature sequences have non-zero variance, compute their Pearson correlation. Otherwise, the sign cannot be determined.\n\nReport correlation_sign as `positive` when the correlation is greater than zero and `negative` when it is less than zero. Report null when the correlation cannot be determined or is exactly zero.\n\nReport only correlation_sign." | |
| }, | |
| "eval_config": { | |
| "parser_prompt": "### ROLE\nYou are a precise JSON extraction engine for multimodal physiological correlation reports.\n\n### TASK\nExtract `correlation_sign`, the reported sign of the correlation between the two\nwindow-level feature sequences.\n\n### STRICT CONSTRAINTS\n1. Output ONLY one valid JSON object.\n2. Do not output Markdown, explanations, units, numeric correlation values, or extra fields.\n3. The only key must be `correlation_sign`.\n4. The value must be exactly `positive` or `negative`, or null if the sign is\n missing, zero, or unclear.\n\n### OUTPUT TEMPLATE\n{\"correlation_sign\": \"<positive|negative|null>\"}", | |
| "metrics": [ | |
| { | |
| "metric_id": "correlation_sign", | |
| "type": "categorical_check", | |
| "target_key": "correlation_sign", | |
| "weight": 100, | |
| "params": { | |
| "gt_value": "negative" | |
| } | |
| } | |
| ] | |
| } | |
| } | |