{"id":"W2901722539","doi":"10.1111/ecin.12739","title":"WHAT DO BICYCLE HELMET LAWS DO? EVIDENCE FROM CANADA","year":2018,"lang":"en","type":"article","venue":"Economic Inquiry","topic":"Injury Epidemiology and Prevention","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Unintended consequences; Population; Injury prevention; Law; Suicide prevention; Human factors and ergonomics; Current Population Survey; Affect (linguistics); Poison control; Cycling; Demographic economics; Psychology; Political science; Demography; Economics; Medicine; Environmental health; Sociology; History","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00389913,0.0005444519,0.0009424292,0.002755993,0.002248764,0.002424193,0.002215883,0.001025383,0.006866382],"category_scores_gemma":[0.02888766,0.0004938198,0.001477619,0.006591043,0.001576652,0.000817234,0.00142824,0.00148196,0.0003711409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0281954,"about_ca_system_score_gemma":0.05717627,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9945977,"about_ca_topic_score_gemma":0.99455,"domain_scores_codex":[0.9958968,0.0008385063,0.0003643644,0.0004966713,0.001446323,0.000957291],"domain_scores_gemma":[0.977612,0.006735099,0.005730222,0.0007928219,0.007277566,0.001852269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008324201,0.0001652155,0.9061928,0.002160683,0.002106898,0.0002484402,0.001187028,0.001299746,0.00005400967,0.004624354,0.03598088,0.04514756],"study_design_scores_gemma":[0.0002336849,0.00008423148,0.9687019,0.003193472,0.002067036,0.00007283803,0.002237644,0.001020022,0.0001283706,0.0009013226,0.02131211,0.00004741831],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6399179,0.1852542,0.0008440476,0.05617119,0.0006675555,0.0003609749,0.05331865,0.00008347486,0.06338215],"genre_scores_gemma":[0.9496073,0.03733857,0.0003124195,0.00301778,0.0001211463,0.00004493706,0.00617603,0.00002020758,0.00336164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0281954,"threshold_uncertainty_score":0.2045729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0594313788062273,"score_gpt":0.3443936804244966,"score_spread":0.2849623016182693,"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."}}