{"id":"W3196648868","doi":"10.1016/j.jsr.2021.08.008","title":"Modelling the relationship of driver license and offense history with fatal and serious injury (FSI) crash involvement","year":2021,"lang":"en","type":"article","venue":"Journal of Safety Research","topic":"Traffic and Road Safety","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Mount Allison University","funders":"","keywords":"Crash; License; Poison control; Injury prevention; Human factors and ergonomics; Occupational safety and health; Computer security; Sample (material); Engineering; Seat belt; Applied psychology; Psychological intervention; Suicide prevention; Transport engineering; Psychology; Computer science; Environmental health; Medicine","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":[0.001582144,0.0008439079,0.0005419662,0.0009141581,0.000378877,0.001782627,0.001386652,0.002014522,0.006790639],"category_scores_gemma":[0.009019201,0.0007179354,0.001144722,0.0007419912,0.0004557933,0.0009818719,0.0007842328,0.001446978,0.000845651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009622767,"about_ca_system_score_gemma":0.00149897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04830088,"about_ca_topic_score_gemma":0.03438835,"domain_scores_codex":[0.9994277,0.0001754684,0.00003734431,0.0001556813,0.00004562805,0.0001581633],"domain_scores_gemma":[0.9892696,0.008809971,0.0007664692,0.0002422789,0.0003934845,0.000518278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008543029,0.001079803,0.3845801,0.00008185411,0.0003773279,0.000448906,0.0002313199,0.6002538,0.001252544,0.001511501,0.0006345849,0.008693902],"study_design_scores_gemma":[0.00003326177,0.0003157837,0.06224914,0.00001921936,0.0001444995,0.0001150068,0.0001879255,0.9352655,0.000337757,0.0008869696,0.000414217,0.00003072969],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940493,0.0001147431,0.003729889,0.0001825625,0.00002295206,0.00002358855,0.0008039299,0.00005040268,0.00102265],"genre_scores_gemma":[0.9973938,0.00004928508,0.0004716506,0.00001153057,0.000006928151,0.00001368296,0.0004632584,0.000006021636,0.001583861],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04830088,"threshold_uncertainty_score":0.09603941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05966969261753043,"score_gpt":0.2730922110254642,"score_spread":0.2134225184079338,"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."}}