{"id":"W4408713264","doi":"10.1109/itsc58415.2024.10919512","title":"Predicting Road Accidents Using Machine Learning Models","year":2024,"lang":"en","type":"article","venue":"","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Machine learning; Artificial intelligence; Transport engineering; 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":[0.0007311427,0.0008264848,0.0004931843,0.001535025,0.0002920289,0.000746751,0.0008685258,0.00067141,0.001331114],"category_scores_gemma":[0.002505181,0.0002613692,0.0006256897,0.001109728,0.000171647,0.0006430869,0.0003898584,0.0008128218,0.0004343718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001069016,"about_ca_system_score_gemma":0.0008643838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0542383,"about_ca_topic_score_gemma":0.03716965,"domain_scores_codex":[0.9996456,0.00009421496,0.00003021238,0.0001023463,0.00006060895,0.00006696316],"domain_scores_gemma":[0.9988404,0.0007230801,0.0001268754,0.00004286995,0.0002194718,0.0000473449],"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":[0.00006615009,0.0001869683,0.02433176,0.00003220573,0.00007255645,0.00004991156,0.00001674935,0.9393526,0.0001366554,0.0003680876,0.001486797,0.0338996],"study_design_scores_gemma":[0.00000155198,0.000009276055,0.00176556,0.000003450075,0.000004631726,0.000003842089,0.00001031311,0.9976829,0.00005614005,0.0003464705,0.0001132867,0.000002618713],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.833936,0.002115144,0.1515614,0.0009712478,0.0002416339,0.0001421221,0.003888383,0.001477115,0.005666904],"genre_scores_gemma":[0.9852228,0.0003180853,0.01026735,0.0000469563,0.00005213977,0.00004702267,0.002423206,0.00001366297,0.001608838],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0542383,"threshold_uncertainty_score":0.1078452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02554221471291366,"score_gpt":0.2425692716976734,"score_spread":0.2170270569847597,"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."}}