{"id":"W4388037728","doi":"10.1109/icidea59866.2023.10295233","title":"Mitigating Truck Driver Fatigue: A Driver Sleepiness Detecting System","year":2023,"lang":"en","type":"article","venue":"","topic":"Sleep and Work-Related Fatigue","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Agra; Truck; Safeguarding; Sleep deprivation; Transport engineering; Falling (accident); Computer security; Engineering; Forensic engineering; Business; Environmental health; Computer science; Psychology; Medicine; Automotive engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003900626,0.0002761716,0.0003137007,0.0002742665,0.0003347466,0.00005994707,0.0003058432,0.0003212946,0.001365658],"category_scores_gemma":[0.00008280179,0.0002538706,0.0001591463,0.001275969,0.0000723081,0.0001306946,0.0001094268,0.0004056573,0.005570172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007954484,"about_ca_system_score_gemma":0.00001799446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002620584,"about_ca_topic_score_gemma":0.00004442503,"domain_scores_codex":[0.9977351,0.0001893079,0.0004933422,0.0005893931,0.0002735192,0.000719381],"domain_scores_gemma":[0.9986977,0.0003690621,0.0001582867,0.000523125,0.00009117212,0.0001606321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001769327,0.0002741839,0.2238383,0.0002357331,0.002681206,0.002068517,0.04495824,0.001219181,0.006519462,0.08330706,0.04632276,0.5883985],"study_design_scores_gemma":[0.03453618,0.001298705,0.6285856,0.0102233,0.001949627,0.0007324737,0.2222044,0.04688405,0.02924587,0.001384101,0.01166629,0.01128945],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9170462,0.00009638952,0.00245182,0.0002323329,0.00272094,0.000385327,0.000006924779,0.002064571,0.07499547],"genre_scores_gemma":[0.9962518,0.000002478918,0.0007189127,0.0001531915,0.0002075119,0.0001044429,0.00002113415,0.00007298918,0.002467512],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.577109,"threshold_uncertainty_score":0.9999914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03408069190959059,"score_gpt":0.3021915948966819,"score_spread":0.2681109029870913,"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."}}