{"id":"W3115683849","doi":"10.3390/risks9010004","title":"Machine Learning in P&C Insurance: A Review for Pricing and Reserving","year":2020,"lang":"en","type":"review","venue":"Risks","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Université Laval","keywords":"Machine learning; Artificial intelligence; Computer science; Artificial neural network; Field (mathematics); State (computer science); Work (physics); Data science; Algorithm; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001332305,0.000835148,0.001451992,0.002803675,0.0003171887,0.001183652,0.000941743,0.001570409,0.004272697],"category_scores_gemma":[0.002816688,0.0003554569,0.0008649955,0.004286773,0.000570617,0.001852262,0.0006707464,0.001819975,0.001860236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008222152,"about_ca_system_score_gemma":0.001612531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002244431,"about_ca_topic_score_gemma":0.002843333,"domain_scores_codex":[0.9996493,0.00009062923,0.00005546037,0.00006646143,0.0001157991,0.00002243124],"domain_scores_gemma":[0.9982644,0.00126848,0.0001317616,0.00003290651,0.0002518555,0.0000507111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005213573,0.00007466332,0.0002887321,0.02042197,0.0001205283,0.00009188818,0.00005264726,0.001034486,0.0003044165,0.01116182,0.03256276,0.933834],"study_design_scores_gemma":[0.00001802348,0.0001262438,0.001322469,0.01422133,0.0002406509,0.000500868,0.00006788438,0.0006835365,0.0002245458,0.009048856,0.9735051,0.00004036511],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00006464523,0.9986618,0.0002416873,0.0003767704,0.0001295952,0.000002782127,0.00001491776,0.000003919071,0.0005039903],"genre_scores_gemma":[0.0006095269,0.9984818,0.0002463947,0.0001858397,0.0002379494,0.000004498272,0.0000214587,0.000001689246,0.000210842],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004272697,"threshold_uncertainty_score":0.01429361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1719013067976391,"score_gpt":0.4468739526080591,"score_spread":0.2749726458104199,"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."}}