{"id":"W3207500430","doi":"10.7307/ptt.v33i5.3782","title":"Prediction of Fatalities in Vehicle Collisions in Canada","year":2021,"lang":"en","type":"article","venue":"PROMET - Traffic&Transportation","topic":"Traffic and Road Safety","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Collision; Exploratory analysis; Predictive modelling; Poison control; Computer science; Transport engineering; Machine learning; Computer security; Engineering; Environmental health; Medicine; Data science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000789045,0.0001002914,0.0001848578,0.0001079268,0.00001712391,0.000004576614,0.00005455727,0.0000608839,0.00004432914],"category_scores_gemma":[0.000008262598,0.0001126311,0.00003029418,0.0005806916,0.00001400394,0.0001356617,0.000001000846,0.0001359582,0.000001001983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001971064,"about_ca_system_score_gemma":0.0003337392,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05783202,"about_ca_topic_score_gemma":0.9000764,"domain_scores_codex":[0.9990536,0.00002000318,0.0004205127,0.0001418831,0.0001891069,0.0001749102],"domain_scores_gemma":[0.9997504,0.00003953362,0.00002840846,0.0001013981,0.00003972672,0.00004055718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0000138178,0.00006562736,0.08192059,0.0002343306,0.00001820518,0.0000467564,0.002219113,0.9101739,0.001213835,0.0002424917,0.0001132,0.003738156],"study_design_scores_gemma":[0.000570117,0.00001408354,0.9643048,0.00009429066,0.00001197123,8.214236e-7,0.001697281,0.02952536,0.003267088,0.00001860591,0.0003888543,0.0001067481],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983541,0.0002654097,0.000216115,0.00004914608,0.0002245268,0.0001536297,0.0005121408,0.00007271383,0.0001522489],"genre_scores_gemma":[0.9989118,0.0001476176,0.0003621783,0.000006217279,0.00001276532,0.00002688688,0.0004903253,0.00001630959,0.00002587894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8823842,"threshold_uncertainty_score":0.9484419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01148693115061188,"score_gpt":0.1806426042851746,"score_spread":0.1691556731345627,"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."}}