{"id":"W4413376283","doi":"10.3390/electronics14163329","title":"Road Accident Analysis and Prevention Using Autonomous Vehicles with Application for Montreal","year":2025,"lang":"en","type":"article","venue":"Electronics","topic":"Traffic and Road Safety","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Aeronautics; Transport engineering; Accident (philosophy); Accident analysis; Computer science; Engineering; Automotive engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003024876,0.0005905632,0.0002444721,0.0009539484,0.0003548365,0.0006059483,0.0005912371,0.0002431165,0.00300469],"category_scores_gemma":[0.0008625022,0.0001963625,0.000527713,0.0008090941,0.0001299079,0.0002933616,0.0003734419,0.0001665073,0.0002404188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001691815,"about_ca_system_score_gemma":0.002077114,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.557532,"about_ca_topic_score_gemma":0.4672108,"domain_scores_codex":[0.9998857,0.00002208257,0.000005140217,0.0000287591,0.00003832965,0.00001996272],"domain_scores_gemma":[0.9998426,0.00004174408,0.00002031826,0.0000131105,0.00006618873,0.00001603323],"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":[0.0001364513,0.0001421156,0.04952968,0.0001204893,0.0001297209,0.0002520416,0.0001114348,0.8452811,0.002775782,0.004140177,0.003523143,0.09385782],"study_design_scores_gemma":[0.000008124918,0.00003155018,0.01099057,0.000006196079,0.00001984079,0.00001607438,0.00005035429,0.9862091,0.0005514217,0.0004102369,0.001692975,0.00001341715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8100639,0.0006839774,0.1545437,0.0003706852,0.00009139079,0.0004856037,0.007118718,0.004449018,0.02219303],"genre_scores_gemma":[0.9587212,0.0003014781,0.03427042,0.00001598357,0.00001228036,0.00009356927,0.002042909,0.00004964585,0.004492586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.442468,"threshold_uncertainty_score":0.8901477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003768431855523309,"score_gpt":0.2256840503872305,"score_spread":0.2219156185317072,"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."}}