{"id":"W4384821089","doi":"10.1080/10920277.2023.2213295","title":"Bowley Insurance with Expected Utility Maximization of the Policyholders","year":2023,"lang":"en","type":"article","venue":"North American Actuarial Journal","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; University of Calgary","keywords":"Indemnity; Expected utility hypothesis; Pareto principle; Underwriting; Economics; Actuarial science; Deductible; Inefficiency; Microeconomics; Mathematical economics; Operations management","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":[],"consensus_categories":[],"category_scores_codex":[0.0002850022,0.0001351007,0.0003492795,0.0002183989,0.0002338661,0.00005243001,0.0003513714,0.000027406,0.00005196013],"category_scores_gemma":[0.0001434998,0.0001056196,0.0001263255,0.001733048,0.0002392664,0.0001864397,0.00005375957,0.000240405,0.00006119181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005976635,"about_ca_system_score_gemma":0.00005894846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008209846,"about_ca_topic_score_gemma":0.000409422,"domain_scores_codex":[0.998793,0.0000312319,0.0005320464,0.0002113263,0.0001118272,0.0003205641],"domain_scores_gemma":[0.9986177,0.00002538031,0.0009091654,0.0003036963,0.00007752611,0.00006650377],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001350207,0.0000456737,0.977257,0.000007768483,0.00005304387,0.000005222834,0.0008809227,0.0008788784,0.000003580966,0.001551665,0.001071499,0.01810975],"study_design_scores_gemma":[0.0005462508,0.000102372,0.9903633,0.00001025687,0.000005907442,0.000005805431,0.0001641921,0.0002819359,0.00002064338,0.0009114661,0.007454077,0.0001338135],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925436,0.00004346043,0.002732778,0.0005666082,0.000561751,0.0001806881,0.00009076756,0.00003399724,0.00324632],"genre_scores_gemma":[0.9988534,0.0003110895,0.0001920547,0.0002203607,0.0002572074,0.000007899787,0.000006721494,0.00001901675,0.0001322796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01797594,"threshold_uncertainty_score":0.4307042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02232304974540712,"score_gpt":0.2119947776038774,"score_spread":0.1896717278584703,"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."}}