{"id":"W4396713572","doi":"10.18280/ria.380106","title":"An Efficient Deep Learning Model Based on Driver Behaviour Detection Within CAN-BUS Signals","year":2024,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Distraction; Convolutional neural network; Deep learning; Artificial intelligence; CAN bus; Artificial neural network; Real-time computing; Machine learning; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002654357,0.0007425737,0.0004896272,0.000394824,0.0002388927,0.0004896489,0.00108372,0.0006061933,0.001425213],"category_scores_gemma":[0.0007053498,0.00028624,0.0004529946,0.000301576,0.0001839006,0.0005252273,0.0006127015,0.001159225,0.0006696146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000610158,"about_ca_system_score_gemma":0.001058122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01657936,"about_ca_topic_score_gemma":0.0157401,"domain_scores_codex":[0.9998655,0.00001276867,0.000007099014,0.00004411623,0.00003297948,0.00003745413],"domain_scores_gemma":[0.9998578,0.00003290602,0.00001364439,0.000009832411,0.00007133913,0.00001443572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002876318,0.000346034,0.005721851,0.0001140595,0.0001161518,0.0001446721,0.00006288201,0.6586247,0.01195327,0.001852017,0.005217723,0.315559],"study_design_scores_gemma":[0.000002757482,0.00001929841,0.0002459291,0.000003272256,0.000006713363,0.000006489302,0.00000260063,0.9984951,0.0008258459,0.0002032608,0.0001860642,0.000002692213],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2458519,0.001656892,0.7375523,0.0009979889,0.0003895799,0.0001646778,0.0007335404,0.003860182,0.008792891],"genre_scores_gemma":[0.9582366,0.0003961615,0.03301236,0.0002676932,0.00004585434,0.0001375207,0.001039574,0.00004385528,0.006820484],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01657936,"threshold_uncertainty_score":0.03296572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01483374345900372,"score_gpt":0.2375611328333608,"score_spread":0.2227273893743571,"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."}}