{"id":"W3125327114","doi":"10.3905/jfi.2017.27.2.065","title":"Reinsurance or CAT Bond? <i>How to Optimally Combine Both</i>","year":2017,"lang":"en","type":"article","venue":"The Journal of Fixed Income","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Reinsurance; Underwriting; Bond; Hedge; Business; Actuarial science; Shareholder; Credit risk; Financial economics; Economics; 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":[0.001843328,0.0001729771,0.0005503547,0.0001712369,0.0005266801,0.000236569,0.001453278,0.00006611898,0.00007825434],"category_scores_gemma":[0.0004505655,0.0001243319,0.0001550847,0.000144531,0.0000989068,0.0005592595,0.0002003447,0.0002467149,0.000267754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00010615,"about_ca_system_score_gemma":0.00004061181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001139567,"about_ca_topic_score_gemma":0.0000630436,"domain_scores_codex":[0.9986644,0.00001947863,0.0007190681,0.0001603971,0.0001049468,0.0003317246],"domain_scores_gemma":[0.9974388,0.00007058505,0.001435818,0.0008393754,0.000103415,0.0001120028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007136097,0.001066126,0.3391981,0.0004012619,0.001094407,0.0008702381,0.006726935,0.003177478,0.001929184,0.314548,0.2835996,0.04025253],"study_design_scores_gemma":[0.002583308,0.001121184,0.6163245,0.0002074534,0.00003741516,0.0001005472,0.0001413493,0.0002894636,0.0005000716,0.01413721,0.3640065,0.000550935],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9342698,0.001269249,0.006047856,0.02737993,0.002431751,0.0004107311,0.00007352109,0.00001955991,0.02809753],"genre_scores_gemma":[0.9907048,0.001124729,0.002335983,0.001482291,0.0003894965,0.000004879749,5.664118e-7,0.00002606239,0.003931156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3004108,"threshold_uncertainty_score":0.5070107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03402354452989591,"score_gpt":0.2452733189546802,"score_spread":0.2112497744247843,"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."}}