{"id":"W2561804198","doi":"10.1111/jori.12172","title":"Dynamic Moral Hazard: A Longitudinal Examination of Automobile Insurance in Canada","year":2016,"lang":"en","type":"article","venue":"Journal of Risk & Insurance","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Spurious relationship; Moral hazard; Context (archaeology); Econometrics; Economics; Actuarial science; Hazard; Panel data; Microeconomics; Statistics; Incentive; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009746198,0.0001866046,0.0006904221,0.0003773347,0.00004614914,0.00001561131,0.0003781712,0.00007038713,0.00004173044],"category_scores_gemma":[0.0002221762,0.0001627614,0.0001430497,0.0004763583,0.00007237097,0.0005460904,0.00003148026,0.0002379654,0.00002008056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001016895,"about_ca_system_score_gemma":0.0002141858,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07663404,"about_ca_topic_score_gemma":0.2711399,"domain_scores_codex":[0.9978113,0.00004244576,0.001429606,0.0002299311,0.0001617142,0.0003250283],"domain_scores_gemma":[0.9978401,0.00011127,0.001558136,0.0002679289,0.0001557928,0.00006675014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006361095,0.00007368736,0.9427999,0.00003985227,0.00003298552,0.00004385257,0.0001669293,0.0009981664,0.00004505481,0.003694124,0.0001342994,0.05190758],"study_design_scores_gemma":[0.001346438,0.00009708459,0.99123,0.0001877034,0.000004471056,0.00001192618,0.00004616805,0.0004285587,0.0001352453,0.00466548,0.001642483,0.0002044506],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914716,0.003881796,0.001859944,0.0001222872,0.0009477952,0.0001377043,0.0004357302,0.000006844895,0.001136306],"genre_scores_gemma":[0.9934695,0.005868369,0.000498087,0.00002598642,0.00005486005,0.000008452884,0.000001073624,0.00002109827,0.00005255333],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1945059,"threshold_uncertainty_score":0.9295147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01312593179293512,"score_gpt":0.2015730232877287,"score_spread":0.1884470914947936,"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."}}