{"id":"W2976790611","doi":"10.1016/j.insmatheco.2019.09.002","title":"Budget-constrained optimal insurance with belief heterogeneity","year":2019,"lang":"en","type":"article","venue":"Insurance Mathematics and Economics","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Deductible; Actuarial science; Indemnity; Event (particle physics); Insurance policy; Reinsurance; Monotone polygon; Consistency (knowledge bases); Econometrics; Economics; Mathematical economics; Complement (music); Simple (philosophy); Mathematics","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":[0.0004565358,0.0003516818,0.0007937626,0.0001618074,0.0001539878,0.0001736603,0.0003100143,0.0001370601,0.00009205982],"category_scores_gemma":[0.00002306874,0.000365956,0.0001204853,0.0001597157,0.0001208537,0.0004391938,0.00009786772,0.0001977657,0.0007718447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007245433,"about_ca_system_score_gemma":0.00002436193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005395858,"about_ca_topic_score_gemma":0.0000473766,"domain_scores_codex":[0.9979573,0.000005935207,0.000832518,0.0006530059,0.00004399626,0.0005071989],"domain_scores_gemma":[0.9986466,0.00005290843,0.0005367106,0.0006076569,0.00004130218,0.0001148548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00006352057,0.0002307538,0.459134,0.0003076131,0.0001492249,0.000007638054,0.0008065565,0.001932442,0.0000269783,0.5337325,0.00005238568,0.003556395],"study_design_scores_gemma":[0.008029738,0.001101972,0.8071082,0.0003683979,0.00003539427,0.000149727,0.0008061195,0.03257319,0.0008315945,0.08351796,0.06201027,0.003467475],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9679549,0.0007068283,0.002328083,0.0001901636,0.0003432913,0.0005461334,0.0003185936,0.00006088401,0.02755111],"genre_scores_gemma":[0.9881813,0.001193572,0.009649777,0.0003166106,0.00008172602,0.00005238239,0.00001295633,0.00005910787,0.0004525547],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4502145,"threshold_uncertainty_score":0.9998792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01406673572131212,"score_gpt":0.1948958727996959,"score_spread":0.1808291370783838,"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."}}