{"id":"W4407795009","doi":"10.1017/asb.2025.1","title":"Worst-case reinsurance strategy with likelihood ratio uncertainty","year":2025,"lang":"en","type":"article","venue":"Astin Bulletin","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Reinsurance; Econometrics; Economics; Statistics; Mathematics; Actuarial science","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":[0.006640493,0.001321597,0.00192688,0.0007992317,0.000505059,0.002332353,0.002518603,0.002562388,0.002476609],"category_scores_gemma":[0.01200988,0.0006244482,0.00116909,0.0006158718,0.002163233,0.002885051,0.001949735,0.001617447,0.0002867029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001948242,"about_ca_system_score_gemma":0.001011753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002091076,"about_ca_topic_score_gemma":0.0008110591,"domain_scores_codex":[0.9962652,0.001890478,0.0001507403,0.0005918466,0.000531543,0.0005701224],"domain_scores_gemma":[0.9920548,0.005113853,0.001272187,0.0005592863,0.0005231688,0.000476691],"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":[0.0001818705,0.00009643688,0.0007868011,0.00005742068,0.00009488681,0.0003872734,0.00009759468,0.9476593,0.001629454,0.04370227,0.000350004,0.004956747],"study_design_scores_gemma":[0.00002646771,0.000132874,0.0003837887,0.00001511464,0.00003256854,0.0001157741,0.00006789795,0.9731845,0.000823113,0.02492391,0.0002698432,0.00002416828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2544211,0.0006212592,0.7333468,0.00117926,0.0000462373,0.0001240598,0.0001545735,0.0001434578,0.009963309],"genre_scores_gemma":[0.9888924,0.0001070934,0.008706744,0.0000510441,0.00001599102,0.00003474249,0.00002807312,0.00001499445,0.002148901],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006640493,"threshold_uncertainty_score":0.0351187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02973231887613184,"score_gpt":0.3240783556594435,"score_spread":0.2943460367833116,"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."}}