{"id":"W4387129780","doi":"10.1111/jori.12449","title":"Mitigating wildfire losses via insurance‐linked securities: Modeling and risk management perspectives","year":2023,"lang":"en","type":"article","venue":"Journal of Risk & Insurance","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Yunnan University; Trường Đại học Kinh tế - Luật, Đại học Quốc gia Thành phố Hồ Chí Minh; Social Sciences and Humanities Research Council of Canada; Yunnan University of Finance and Economics; Zhongnan University of Economics and Law","keywords":"Reinsurance; Bond; Hedge; Risk management; Liability; Scope (computer science); Actuarial science; Model risk; Computer science; Business; Risk analysis (engineering); Environmental resource management; Environmental science; Finance; Ecology","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":[0.001626438,0.0006299954,0.0007418547,0.0005041999,0.0002892665,0.002024493,0.001183666,0.001576196,0.00192444],"category_scores_gemma":[0.003461918,0.0003273511,0.0006055782,0.0004466601,0.0007782358,0.002036969,0.000847983,0.001376205,0.0001065896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000787601,"about_ca_system_score_gemma":0.0009857833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006071652,"about_ca_topic_score_gemma":0.004226473,"domain_scores_codex":[0.9996773,0.0001500537,0.00001205815,0.00004839819,0.00006702789,0.00004527901],"domain_scores_gemma":[0.9986367,0.000744214,0.0003287526,0.00007000901,0.0001364538,0.00008391801],"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":[0.00001863136,0.00006186697,0.001938559,0.0000220308,0.00002726081,0.00006097122,0.00003893522,0.8938,0.0004567589,0.0983022,0.0005569354,0.004715947],"study_design_scores_gemma":[0.000003245004,0.0000195867,0.0001796509,0.000008760073,0.000007120517,0.00001438472,0.00001457153,0.981921,0.00007530199,0.01739503,0.0003560944,0.000005276925],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3446664,0.002881814,0.6244334,0.004726984,0.000133936,0.00009220256,0.0003740784,0.0002222263,0.02246901],"genre_scores_gemma":[0.9808905,0.0009817948,0.01445743,0.00007736191,0.00006608658,0.00003414994,0.00005855488,0.00001182232,0.003422297],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006071652,"threshold_uncertainty_score":0.01207262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01566629976410396,"score_gpt":0.222055684927044,"score_spread":0.2063893851629401,"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."}}