{"id":"W4365788309","doi":"10.1109/incoft55651.2022.10094418","title":"An Efficient Detection of Driver Tiredness and Fatigue using Deep Learning","year":2022,"lang":"en","type":"article","venue":"","topic":"Sleep and Work-Related Fatigue","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Convolutional neural network; ALARM; Computer science; Automotive industry; Computer security; Deep learning; Artificial intelligence; Risk analysis (engineering); Engineering; Business","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001813778,0.00007409835,0.00009848097,0.0001118511,0.0002552491,0.000008305503,0.00006776075,0.00005533337,0.00130037],"category_scores_gemma":[0.000006965553,0.00007492155,0.00002616877,0.0002330773,0.00004238576,0.00002881688,0.00004525759,0.0002249577,0.000005320171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003213573,"about_ca_system_score_gemma":0.000005183891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003566025,"about_ca_topic_score_gemma":0.00001704157,"domain_scores_codex":[0.9991853,0.0001995392,0.0001472518,0.0002045343,0.0001177658,0.0001456489],"domain_scores_gemma":[0.9996797,0.00004131879,0.00007319087,0.0001386747,0.00002331727,0.00004382042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002540321,0.0006458437,0.07258866,0.000007970727,0.0002162164,0.00003190696,0.02674207,0.4332896,0.04991907,0.004582651,0.00002275796,0.4116992],"study_design_scores_gemma":[0.007302326,0.003033472,0.1204539,0.00007536159,0.0004512695,0.0001767578,0.08325111,0.7628604,0.01966935,0.0001186644,0.001111937,0.001495462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9718024,0.000169878,0.02469361,0.000007618085,0.0004747458,0.00009932349,7.768331e-7,0.00005806173,0.002693575],"genre_scores_gemma":[0.9996487,0.000001119929,0.0001979945,0.00002488321,0.00002112053,0.00001015623,0.000003812561,0.00001423786,0.00007797797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4102038,"threshold_uncertainty_score":0.9996126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02778755511877459,"score_gpt":0.3056265308022436,"score_spread":0.277838975683469,"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."}}