{"id":"W1988552592","doi":"10.1002/asmb.1981","title":"Multivariate risk models under heavy‐tailed risks","year":2013,"lang":"en","type":"article","venue":"Applied Stochastic Models in Business and Industry","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Copula (linguistics); Multivariate statistics; Mathematics; Risk model; Econometrics; Net (polyhedron); Ruin theory; Multivariate normal distribution; Statistics; Applied mathematics; Economics; Mathematical economics","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":[0.006572691,0.001450312,0.001999588,0.0013798,0.000693245,0.002647941,0.002725675,0.00256769,0.003924842],"category_scores_gemma":[0.01480625,0.000832137,0.001441508,0.001212325,0.00250637,0.004715524,0.002245938,0.004039065,0.0005317078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001548779,"about_ca_system_score_gemma":0.0008978058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005512557,"about_ca_topic_score_gemma":0.003128367,"domain_scores_codex":[0.9970698,0.001161546,0.0001365733,0.0005288617,0.0005710788,0.0005319843],"domain_scores_gemma":[0.9882487,0.007291233,0.002405331,0.0008110924,0.0007005155,0.0005431815],"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":[0.0001163628,0.0001080462,0.003616654,0.00009179598,0.00009854322,0.0004743543,0.0002570953,0.5461093,0.00126506,0.4370734,0.001160691,0.009628682],"study_design_scores_gemma":[0.00001994771,0.00004138374,0.001012363,0.00001612718,0.00002950705,0.000110459,0.00004147576,0.8903548,0.0002268792,0.1076043,0.0005068916,0.00003586468],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1476575,0.001294884,0.8425674,0.0015734,0.00009123949,0.00007505778,0.0003297724,0.0002880919,0.006122744],"genre_scores_gemma":[0.9696003,0.001079788,0.01949104,0.0001328128,0.000220093,0.0001151497,0.0001852917,0.00004900072,0.009126602],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006572691,"threshold_uncertainty_score":0.03476012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1735913572905731,"score_gpt":0.3451613400150841,"score_spread":0.1715699827245111,"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."}}