{"id":"W3123741628","doi":"10.1017/asb.2017.4","title":"COLLECTIVE RISK MODELS WITH DEPENDENCE UNCERTAINTY","year":2017,"lang":"en","type":"article","venue":"Astin Bulletin","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Eidgenössische Technische Hochschule Zürich","keywords":"Econometrics; Portfolio; Expected shortfall; Equivalence (formal languages); Aggregate (composite); Value at risk; Economics; Risk model; Random variable; Copula (linguistics); Mathematics; Statistical physics; Actuarial science; Statistics; Risk management; Physics; Financial economics","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":[0.005185852,0.0009618606,0.0016764,0.001302071,0.0007233467,0.002097921,0.002144043,0.002286543,0.002582785],"category_scores_gemma":[0.01777367,0.0005736273,0.001426443,0.001022783,0.003091106,0.003383116,0.003012101,0.002992258,0.0002319806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001771897,"about_ca_system_score_gemma":0.0006621974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003684298,"about_ca_topic_score_gemma":0.001596771,"domain_scores_codex":[0.9965744,0.001352008,0.0001104726,0.0005438701,0.000998904,0.0004203472],"domain_scores_gemma":[0.9831603,0.01084901,0.002933317,0.001288085,0.001100871,0.0006683448],"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":[0.00005021082,0.00004323835,0.001851639,0.000047405,0.00008413864,0.000320151,0.0001576115,0.7887288,0.0005106812,0.2037525,0.0009915357,0.00346213],"study_design_scores_gemma":[0.000005957035,0.00002100419,0.0003448233,0.0000117766,0.00001399654,0.00004492969,0.00002338802,0.9062729,0.000100655,0.09280485,0.0003415759,0.00001415972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2005928,0.001089951,0.7803754,0.002797379,0.0001456319,0.00003973633,0.0002735371,0.000161708,0.01452401],"genre_scores_gemma":[0.9866725,0.0002740555,0.008379039,0.000113593,0.0001002061,0.0000499056,0.0000870536,0.0000277002,0.004295863],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005185852,"threshold_uncertainty_score":0.02742577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1116563641490978,"score_gpt":0.3424084828595605,"score_spread":0.2307521187104627,"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."}}