{"id":"W4416707208","doi":"10.1109/tits.2025.3633499","title":"Driver State Classification: Identifying High Cognitive Load and Drowsiness Through Driver Performance and Physiology","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Sleep and Work-Related Fatigue","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cognition; Driving simulator; Cognitive load; Arousal; Recall; Standard deviation; Effects of sleep deprivation on cognitive performance; Steering wheel; Elementary cognitive task","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004321391,0.0005712653,0.0003334269,0.0006171568,0.0001451651,0.0006737518,0.0001861159,0.0004814269,0.0006133921],"category_scores_gemma":[0.001701573,0.0001343479,0.0002800016,0.0002311774,0.0001062912,0.0004582048,0.000328111,0.000216935,0.0002723316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001140473,"about_ca_system_score_gemma":0.0001337895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002036259,"about_ca_topic_score_gemma":0.001991532,"domain_scores_codex":[0.9998042,0.00003412456,0.00002274181,0.00005270461,0.00005303218,0.00003313296],"domain_scores_gemma":[0.9994623,0.0001838233,0.0001317316,0.00004096577,0.0001096066,0.00007151093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001841266,0.0008298741,0.8164985,0.0001617011,0.0002547202,0.0001598692,0.0007158087,0.002855752,0.0584714,0.00008617183,0.0003649576,0.11776],"study_design_scores_gemma":[0.00001707492,0.0007834052,0.9827355,0.00001147578,0.000054043,0.0001659332,0.0002555749,0.0123238,0.003322304,0.00009940236,0.0002083878,0.0000229899],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974731,0.00005538996,0.002017539,0.00001252968,0.00000559127,0.00002025828,0.000121522,0.00002620722,0.0002678755],"genre_scores_gemma":[0.9980533,0.00005752726,0.00130922,0.00001178353,0.00001104232,0.00002084803,0.0003442848,0.000003700064,0.0001882752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002036259,"threshold_uncertainty_score":0.004048824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03798165093754652,"score_gpt":0.3072315874268108,"score_spread":0.2692499364892643,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}