{"id":"W3004083991","doi":"10.1155/2020/2593410","title":"Examining the Environmental, Vehicle, and Driver Factors Associated with Crossing Crashes of Elderly Drivers Using Association Rules Mining","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic and Road Safety","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Mitsui Sumitomo Insurance Welfare Foundation","keywords":"Crash; Transport engineering; Intersection (aeronautics); Level crossing; Daylight; Poison control; Human factors and ergonomics; Truck; Engineering; Computer security; Environmental health; Computer science; Automotive engineering; Medicine","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":[0.001310073,0.0005432713,0.0005576499,0.0032864,0.000360758,0.0006716708,0.0003550256,0.0003782091,0.0004996658],"category_scores_gemma":[0.003466324,0.0001814134,0.0009973045,0.002211946,0.0001383982,0.0005646979,0.00046168,0.0003637303,0.0001399755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002317222,"about_ca_system_score_gemma":0.0006230165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009839723,"about_ca_topic_score_gemma":0.01141382,"domain_scores_codex":[0.999265,0.0001546606,0.0001734819,0.0001781832,0.000150321,0.00007832026],"domain_scores_gemma":[0.9976832,0.001005686,0.0006747111,0.000129996,0.000404972,0.000101467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005391449,0.00006648268,0.9830548,0.00005167041,0.0001578275,0.0002287594,0.0001273693,0.001141023,0.0004089761,0.00004977257,0.0001968279,0.01446245],"study_design_scores_gemma":[0.00001072313,0.0001460171,0.9621333,0.00007114597,0.0005632346,0.0005619829,0.001549585,0.03225607,0.001152374,0.0004512695,0.001076566,0.00002779929],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953904,0.0004437954,0.003064168,0.00007726834,0.00001056741,0.00003263742,0.0007157417,0.00001773322,0.0002476818],"genre_scores_gemma":[0.9952254,0.0003689508,0.002890509,0.00002191083,0.0000110435,0.00002600762,0.001290428,0.000002599077,0.0001631642],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009839723,"threshold_uncertainty_score":0.01956487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01619220075412416,"score_gpt":0.1988876148535143,"score_spread":0.1826954140993901,"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."}}