{"id":"W4410557920","doi":"10.1016/j.insmatheco.2025.103113","title":"Learning from COVID-19: A catastrophe mortality bond solution in the post-pandemic era","year":2025,"lang":"en","type":"article","venue":"Insurance Mathematics and Economics","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; University of Guelph","funders":"Fundamental Research Funds for the Central Universities; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Virology; Medicine; Outbreak; Infectious disease (medical specialty); Disease","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":[0.001387459,0.0005394298,0.0009951271,0.0003118407,0.0008034203,0.001419372,0.001038118,0.002701264,0.01352719],"category_scores_gemma":[0.010403,0.0002648323,0.0005042059,0.0002926248,0.001075041,0.002106362,0.001999324,0.00282563,0.0003758585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000710146,"about_ca_system_score_gemma":0.001370504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004105778,"about_ca_topic_score_gemma":0.003852943,"domain_scores_codex":[0.9997894,0.00009149173,0.000007272411,0.00003747026,0.00002384768,0.00005058868],"domain_scores_gemma":[0.9974245,0.001724336,0.000203069,0.0001092204,0.0001632427,0.0003756238],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002277038,0.0001459083,0.002129729,0.0001149923,0.00005289515,0.0002759092,0.0002397691,0.2884896,0.0002953273,0.6704282,0.01911149,0.01848847],"study_design_scores_gemma":[0.0000649247,0.00006914199,0.0003938162,0.00003272593,0.00001617336,0.00003590691,0.0001843388,0.5035703,0.00009530353,0.4930435,0.002478051,0.00001585545],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5424341,0.001550116,0.3297508,0.03646661,0.0007599023,0.0001186836,0.0007454269,0.0002449073,0.0879293],"genre_scores_gemma":[0.9613572,0.00053563,0.01530611,0.0006614873,0.0002934686,0.00008114483,0.0002242648,0.00008944432,0.02145121],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01352719,"threshold_uncertainty_score":0.04525292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05968253874100479,"score_gpt":0.3088475618005159,"score_spread":0.2491650230595111,"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."}}