{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003731519,0.0004025788,0.001908248,0.0002811849,0.0005077842,0.0001294637,0.0005795821,0.0002459353,0.00003443343],"category_scores_gemma":[0.001569782,0.0003718395,0.0004386255,0.001389213,0.0001439483,0.0001668837,0.0002421427,0.0008671228,0.00002729336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000181322,"about_ca_system_score_gemma":0.0002130173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003593893,"about_ca_topic_score_gemma":0.004509333,"domain_scores_codex":[0.9962364,0.001081527,0.0008842052,0.0007069646,0.0005064307,0.0005845151],"domain_scores_gemma":[0.9983304,0.0004852494,0.0006219253,0.0003363337,0.00007974702,0.000146397],"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":[0.000002887121,0.00001717517,0.003812097,0.06178062,0.00006396572,0.00001079947,0.0006762939,0.000001487422,8.893543e-9,0.0009170761,0.0005709643,0.9321466],"study_design_scores_gemma":[0.000150283,0.0000192334,0.0004638043,0.04291286,0.0002873853,0.000001321567,0.00006889791,0.00001253525,4.695101e-9,0.000213476,0.9555025,0.0003677177],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00001560633,0.9897777,0.00008315618,0.000432625,0.0002472659,0.00346397,0.00004789808,0.0001308513,0.005800938],"genre_scores_gemma":[0.0001117402,0.9977074,0.0006599282,0.000228094,0.0002995038,0.0004734434,0.00006197012,0.00006361279,0.0003942996],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9549315,"threshold_uncertainty_score":0.9998733,"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."}}