{"id":"W7097934315","doi":"","title":"Myths and Facts about Automobile Insurance in Canada","year":2006,"lang":"en","type":"article","venue":"","topic":"Occupational and Professional Licensing Regulation","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Odds; Appeal; Mythology; Risk management; Disadvantage; Liability insurance","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007550071,0.00005055949,0.0001035111,0.00005264146,0.00003569723,0.00001217331,0.00002865632,0.00002513218,0.0001443977],"category_scores_gemma":[0.0000105681,0.00005212962,0.000009010042,0.0000887951,0.00001007759,0.00009576271,0.00001106301,0.00004133234,0.00002936657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001143211,"about_ca_system_score_gemma":0.00007057305,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8240897,"about_ca_topic_score_gemma":0.7792264,"domain_scores_codex":[0.9995137,0.000004051564,0.0002253741,0.0001351472,0.00002253487,0.00009912701],"domain_scores_gemma":[0.9998084,0.00003753793,0.00006802168,0.00005524736,0.00001052886,0.0000202665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003558142,0.000008746474,0.9010915,0.00000556234,0.000001050397,9.280041e-7,0.00001166724,0.0003397556,0.000005452242,0.0962092,0.001474107,0.0008485346],"study_design_scores_gemma":[0.000153695,0.000003102168,0.963468,0.000006448573,1.408053e-7,7.946178e-7,0.000006821715,0.001628982,0.00002925449,0.01692318,0.01770573,0.00007392158],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9576535,0.0006051824,0.00004407965,0.0005480728,0.0001535317,0.0000567053,0.0000559891,0.000008215271,0.04087479],"genre_scores_gemma":[0.9973063,0.00001095606,0.0002562877,0.0003110558,0.00003412196,0.00000340945,0.00002129882,0.000004116209,0.002052444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07928602,"threshold_uncertainty_score":0.2248022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01059528518845377,"score_gpt":0.1859894555736417,"score_spread":0.175394170385188,"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."}}