{"id":"W4408712208","doi":"10.1109/itsc58415.2024.10919998","title":"Advancing Road Safety: Road Accident Severity Prediction Using Deep Learning Models","year":2024,"lang":"en","type":"article","venue":"","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Road accident; Computer science; Road traffic accident; Accident (philosophy); Transport engineering; Deep learning; Road traffic; Road map; Predictive modelling; Artificial intelligence; Engineering; Machine learning; Geography; Cartography","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":[],"consensus_categories":[],"category_scores_codex":[0.0002402486,0.0001656476,0.0001322523,0.0002031552,0.0001039395,0.0001173319,0.00009344683,0.00008719243,0.00008045672],"category_scores_gemma":[0.00000846313,0.0001726622,0.00007408429,0.0002358131,0.00001153547,0.0008378897,0.00006217408,0.0002949708,0.00002572601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002793178,"about_ca_system_score_gemma":0.00001072911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007385483,"about_ca_topic_score_gemma":0.00004478087,"domain_scores_codex":[0.9990191,0.00002243453,0.0002632353,0.000235439,0.0001923434,0.0002674797],"domain_scores_gemma":[0.9997362,0.00001129786,0.0000136725,0.0001446382,0.00001960748,0.00007457488],"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":[0.000003419984,0.000006240513,0.00006378155,0.00006980998,0.00005199456,0.000008672068,0.000213388,0.7238567,0.0008719597,0.0007775652,0.001945706,0.2721308],"study_design_scores_gemma":[0.00008107212,0.00001526816,0.0008455188,0.0000978096,0.00003465761,0.00001415351,0.0001654349,0.9841233,0.0003968214,0.0001669607,0.01390007,0.0001589186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01840333,0.000714607,0.9292603,0.00003748994,0.0008787274,0.0002032904,0.000002436703,0.02364442,0.02685539],"genre_scores_gemma":[0.9922341,0.0008731059,0.00630237,0.00003298845,0.0001437881,0.00001798285,0.00001583217,0.00004837325,0.0003315353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9738307,"threshold_uncertainty_score":0.704096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01152640034584516,"score_gpt":0.2301064421734029,"score_spread":0.2185800418275577,"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."}}