{"id":"W4391951328","doi":"10.1139/cjce-2023-0446","title":"Using explainable AI for enhanced understanding of winter road safety: insights with support vector machines and SHAP","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Winter Sports Injuries and Performance","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Support vector machine; Computer science; Engineering; Artificial intelligence; Transport engineering; Construction engineering; Operations research; Forensic engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000121395,0.0001139642,0.0002684593,0.0003516215,0.00004561039,0.00003817571,0.00004629575,0.00003949598,0.000115764],"category_scores_gemma":[0.00001851753,0.00008827767,0.00006193557,0.0001222296,0.00003404068,0.0002344664,0.000004948123,0.0001653807,1.404474e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002187802,"about_ca_system_score_gemma":0.0005212412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001992767,"about_ca_topic_score_gemma":0.008813928,"domain_scores_codex":[0.9993414,0.000002168078,0.0002767111,0.00008709435,0.0000906649,0.0002019317],"domain_scores_gemma":[0.9995071,0.00002109414,0.00005848342,0.00006969265,0.00007975566,0.0002638304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.008987253,0.0002290808,0.05724462,0.05695314,0.01201499,0.01750398,0.1629072,0.2574606,0.3036701,0.05538313,0.03040925,0.03723661],"study_design_scores_gemma":[0.009776016,0.009066298,0.01981317,0.04371276,0.00207092,0.01335586,0.005629919,0.5720668,0.04782414,0.001086367,0.2732996,0.002298101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6743498,0.004219902,0.31703,0.0007581416,0.00151478,0.0002907655,0.0000313998,0.00002244768,0.001782738],"genre_scores_gemma":[0.9987858,0.000029663,0.000674993,0.0000546597,0.0002731882,0.000001081861,0.000002292164,0.00002929344,0.0001490628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3244359,"threshold_uncertainty_score":0.4918379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01861096461988939,"score_gpt":0.2446888868255055,"score_spread":0.2260779222056161,"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."}}