{"id":"W2413762583","doi":"10.1080/00330124.2016.1184987","title":"Characterizing and Predicting Traffic Accidents in Extreme Weather Environments","year":2016,"lang":"en","type":"article","venue":"The Professional Geographer","topic":"Traffic and Road Safety","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Meteorology; Geography; Environmental science; Transport engineering; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004147124,0.0004486159,0.0002677214,0.0008725583,0.0003177498,0.0008540314,0.0003133508,0.0005589871,0.000252155],"category_scores_gemma":[0.002146824,0.0002620688,0.0003180632,0.0005999057,0.0001991011,0.0005085638,0.000388345,0.0003110971,0.0001061498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005147012,"about_ca_system_score_gemma":0.0007471456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05424371,"about_ca_topic_score_gemma":0.06442178,"domain_scores_codex":[0.9998116,0.00004416896,0.00001567018,0.0000481702,0.00003008914,0.00005040242],"domain_scores_gemma":[0.99929,0.0002967786,0.000205443,0.00003918884,0.0001067629,0.00006174238],"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":[0.00006890859,0.000198927,0.3244048,0.00001569189,0.00006036751,0.0001706744,0.0001047234,0.6618804,0.0008925067,0.0002898945,0.000500935,0.01141224],"study_design_scores_gemma":[0.000003247767,0.0000425804,0.05636208,0.000004515095,0.00001213922,0.00002990442,0.0002537097,0.9423257,0.0003681087,0.0004005418,0.0001882662,0.000009140089],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955443,0.00002692062,0.003999789,0.00003479839,0.000005014268,0.0000105699,0.0001210366,0.00003736795,0.000220217],"genre_scores_gemma":[0.9977431,0.00004892166,0.001619919,0.000003715977,0.000004721279,0.000006386757,0.0004036397,0.000003320409,0.0001663033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05424371,"threshold_uncertainty_score":0.107856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01581435206751826,"score_gpt":0.2083480046991076,"score_spread":0.1925336526315893,"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."}}