{"id":"W4221117580","doi":"10.1017/asb.2022.4","title":"FUNCTIONAL PROFILE TECHNIQUES FOR CLAIMS RESERVING","year":2022,"lang":"en","type":"article","venue":"Astin Bulletin","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Parametric statistics; Outlier; Robustness (evolution); Range (aeronautics); Scope (computer science); Cover (algebra); Data mining; Mathematical optimization; Artificial intelligence; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00568349,0.0008035701,0.0009138057,0.002206488,0.0004812991,0.001314585,0.002135935,0.0011506,0.003081372],"category_scores_gemma":[0.01632965,0.000468424,0.001433916,0.001332058,0.001129345,0.002276415,0.002175021,0.002155956,0.0008202357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008626785,"about_ca_system_score_gemma":0.000961463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002272274,"about_ca_topic_score_gemma":0.001197012,"domain_scores_codex":[0.9980091,0.001092312,0.0001103396,0.000198215,0.000457409,0.0001326153],"domain_scores_gemma":[0.9910999,0.006052361,0.0005984306,0.001066206,0.0009658635,0.0002172775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000175428,0.0001117739,0.00242003,0.0001700358,0.00006191585,0.0001185443,0.0002049508,0.7310877,0.002159694,0.09408215,0.001599792,0.1678079],"study_design_scores_gemma":[0.000002280892,0.00002246842,0.0002429199,0.000009967372,0.00000321683,0.00002447813,0.00001390564,0.9857476,0.0003370109,0.01313487,0.0004547582,0.000006435848],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007633733,0.0001393237,0.9911125,0.00008639476,0.00001588163,0.00002826508,0.00004047202,0.0001562314,0.0007870989],"genre_scores_gemma":[0.6299012,0.0004857623,0.3654709,0.0001063831,0.0001125239,0.0002746898,0.0004097656,0.0002052609,0.003033592],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00568349,"threshold_uncertainty_score":0.03005755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1522045467154931,"score_gpt":0.3592444055287675,"score_spread":0.2070398588132744,"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."}}