{"id":"W1680930251","doi":"10.1016/j.cageo.2009.06.010","title":"Pricing index-based catastrophe bonds: Part 1","year":2009,"lang":"en","type":"article","venue":"Computers & Geosciences","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Libor; Computer science; Index (typography); Discretization; Callable bond; Reinsurance; Bond; Coupon; Interest rate; Mathematical optimization; Economics; Mathematics; Actuarial science; Finance","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":[0.0004306096,0.0001351141,0.0002411008,0.0002141648,0.0002472609,0.0001540179,0.000475117,0.00004133134,0.00003882201],"category_scores_gemma":[0.00003268357,0.0001420067,0.00006911159,0.000513598,0.00009921657,0.0002771727,0.00003964172,0.00009379126,0.0002090506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005129576,"about_ca_system_score_gemma":0.00002680772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001699217,"about_ca_topic_score_gemma":0.00001200612,"domain_scores_codex":[0.9987038,0.000007385967,0.0003719559,0.0004448132,0.00007392227,0.0003980958],"domain_scores_gemma":[0.9994031,0.00002605757,0.0002102719,0.0002766747,0.00001489504,0.00006898252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004052035,0.0005053537,0.2553416,0.00004129974,0.00002401944,0.0000552462,0.001176106,0.01631195,0.00002052476,0.3427522,0.02129887,0.3624323],"study_design_scores_gemma":[0.0005602467,0.0004088438,0.437487,0.0000468219,0.000003781993,0.000001685039,0.00007186396,0.05836675,0.0000438384,0.02096502,0.4815431,0.000501051],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.502346,0.001607987,0.4583401,0.002914094,0.00319842,0.0004218563,0.00004685015,0.0001906944,0.03093394],"genre_scores_gemma":[0.9939929,0.0000769085,0.003370424,0.002168465,0.0001749083,0.000006198286,0.000006792511,0.000005118225,0.0001982514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4916469,"threshold_uncertainty_score":0.5790865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02073021770264893,"score_gpt":0.2093157793269592,"score_spread":0.1885855616243103,"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."}}