{"id":"W4318037436","doi":"10.1109/gcaiot57150.2022.10019160","title":"Enhanced ALIVE Mind Controller and Machine Learning to Detect Drowsiness While Driving","year":2022,"lang":"en","type":"article","venue":"","topic":"Sleep and Work-Related Fatigue","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Collège de Maisonneuve; Laboratoire Recherche Informatique Maisonneuve","funders":"","keywords":"Headset; Computer science; Bluetooth; Artificial intelligence; Artificial neural network; Simulation; Controller (irrigation); Real-time computing; Wireless","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002753641,0.0004496387,0.0003115272,0.0005753511,0.0001778598,0.000376519,0.0006978166,0.000435932,0.00173694],"category_scores_gemma":[0.0008189857,0.0001868681,0.0002786748,0.0001720901,0.0001718225,0.0005042845,0.0004129343,0.0003737165,0.0003324607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002549607,"about_ca_system_score_gemma":0.0002357385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001509327,"about_ca_topic_score_gemma":0.002417341,"domain_scores_codex":[0.9998554,0.00001916029,0.000007173086,0.00005437072,0.00004237923,0.00002144142],"domain_scores_gemma":[0.9997388,0.0000868346,0.00003127665,0.00003254928,0.00008386661,0.00002673364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001066226,0.001007622,0.01602369,0.0002062508,0.0002752915,0.0004977127,0.0002830343,0.06343487,0.1753448,0.002263159,0.004035681,0.7355617],"study_design_scores_gemma":[0.00005832622,0.0006444009,0.0127869,0.0000194,0.00008033443,0.0003086891,0.00004280962,0.9423289,0.03913691,0.002036375,0.002511707,0.00004532619],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2828338,0.000431381,0.704254,0.0002070367,0.0002099898,0.0002463915,0.0002165179,0.006884797,0.004716036],"genre_scores_gemma":[0.9191634,0.00006913518,0.0780993,0.0001449187,0.0000265822,0.00009501711,0.0001433213,0.00004947385,0.002208737],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00173694,"threshold_uncertainty_score":0.005810618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01642377684875443,"score_gpt":0.2652107390863201,"score_spread":0.2487869622375657,"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."}}