{"id":"W3109734188","doi":"10.1139/cjce-2018-0785","title":"Statistics and prediction of vehicle–bridge collisions in Quebec","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Traffic and Road Safety","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Ministère des Transports; Université de Sherbrooke","funders":"","keywords":"Bridge (graph theory); Speed limit; Georeference; Transport engineering; Road surface; Computer science; Database; Engineering; Geography; Civil 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001051635,0.0003816277,0.0003115046,0.002194022,0.0005652067,0.0009464992,0.0009696189,0.0004783428,0.002499952],"category_scores_gemma":[0.003773049,0.0001778996,0.0004306837,0.002415728,0.0003597082,0.0003466448,0.000421733,0.0004516031,0.0003659295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009076905,"about_ca_system_score_gemma":0.005174271,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9748321,"about_ca_topic_score_gemma":0.9674373,"domain_scores_codex":[0.9995646,0.00007067507,0.00003149381,0.0001190358,0.0001114956,0.000102682],"domain_scores_gemma":[0.9972554,0.0007838897,0.0004127709,0.0001807269,0.001225351,0.0001419604],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009964474,0.00006719185,0.9105281,0.000042924,0.0001373705,0.0001658168,0.0001897804,0.06306644,0.0006133343,0.0006441051,0.005861747,0.01858358],"study_design_scores_gemma":[0.000008308242,0.00003555452,0.7676329,0.00002731913,0.0000281477,0.00004978887,0.0004536468,0.2277618,0.000339941,0.0001638112,0.003471237,0.00002758914],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9693034,0.0003548496,0.005140876,0.0002262956,0.0000179418,0.00006619359,0.02235695,0.0001949693,0.002338634],"genre_scores_gemma":[0.9836792,0.0001123003,0.00153165,0.0000241476,0.000004938549,0.00002911607,0.01301544,0.0000153363,0.001587759],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02516788,"threshold_uncertainty_score":0.06585789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008584860855367507,"score_gpt":0.168637689582695,"score_spread":0.1600528287273275,"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."}}