{"id":"W4402370383","doi":"10.1111/jori.12490","title":"Insurtech, sensor data, and changes in customers' coverage choices: Evidence from usage‐based automobile insurance","year":2024,"lang":"en","type":"article","venue":"Journal of Risk & Insurance","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Automobile insurance; Business; Computer science; Actuarial science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002217537,0.0003400561,0.0008897712,0.0007453995,0.0001797008,0.0002455138,0.0008579386,0.0001814524,0.00007320228],"category_scores_gemma":[0.000686008,0.00034264,0.0001408012,0.0009288131,0.0001392485,0.001634691,0.0002021598,0.0008402647,0.0001249561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002275239,"about_ca_system_score_gemma":0.00009206221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001683023,"about_ca_topic_score_gemma":0.0009117606,"domain_scores_codex":[0.9972067,0.00009211487,0.001287124,0.0007475269,0.0002113706,0.0004551142],"domain_scores_gemma":[0.997317,0.0007023655,0.001016291,0.0007471834,0.00009116313,0.0001260202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002215729,0.0001597953,0.9376811,0.0002654149,0.000114039,0.0003770911,0.001756426,0.001504255,0.0001349575,0.001001221,0.0005272073,0.05625692],"study_design_scores_gemma":[0.001106558,0.0001613802,0.8326998,0.001403969,0.0000229482,0.00001395878,0.00007454932,0.00727583,0.0001368713,0.002532038,0.1541279,0.0004441826],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.915457,0.07677311,0.002848872,0.0005194212,0.001488987,0.0002784361,0.002201052,0.00004622305,0.0003868785],"genre_scores_gemma":[0.9375278,0.06033749,0.001209006,0.0003138788,0.0004634974,0.00001612621,0.00001434072,0.00004502986,0.00007283969],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1536007,"threshold_uncertainty_score":0.9999025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03565796952643876,"score_gpt":0.2617261981152976,"score_spread":0.2260682285888588,"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."}}