{"id":"W4407971656","doi":"10.3390/risks13030044","title":"Copula-Based Risk Aggregation and the Significance of Reinsurance","year":2025,"lang":"en","type":"article","venue":"Risks","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Copula (linguistics); Reinsurance; Econometrics; Actuarial science; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007698087,0.0000882765,0.0002812777,0.0001048223,0.0001330766,0.00002449753,0.0001514366,0.00005163789,0.0000161889],"category_scores_gemma":[0.0002195636,0.00007686242,0.00007372515,0.0002973038,0.0001867479,0.00006617411,0.00002648947,0.0001118964,0.00002936712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002594416,"about_ca_system_score_gemma":0.00001496915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001743357,"about_ca_topic_score_gemma":0.00006239883,"domain_scores_codex":[0.9991778,0.00002948276,0.0004097449,0.0002210241,0.00002996538,0.0001319574],"domain_scores_gemma":[0.9991622,0.0001164454,0.0003761217,0.0002998457,0.00003180868,0.00001358958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001620152,0.00003460546,0.2698134,0.00007147648,0.00003379674,6.14132e-7,0.0001513906,0.0008974817,0.000002844373,0.6912555,0.0005793147,0.03699751],"study_design_scores_gemma":[0.003265015,0.0000417586,0.7408846,0.00007528528,0.00002611705,1.216067e-7,0.00005099282,0.015591,0.000723244,0.1905337,0.04861126,0.0001969403],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.85075,0.01470284,0.07584755,0.001829656,0.000712564,0.001111135,0.0002124389,0.00004575233,0.05478802],"genre_scores_gemma":[0.997067,0.001713963,0.0003648004,0.0002634439,0.00002549666,0.00005664037,0.000003039037,0.000006268021,0.000499313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5007218,"threshold_uncertainty_score":0.3134359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02308841881160701,"score_gpt":0.2382545352430784,"score_spread":0.2151661164314713,"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."}}