{"id":"W2204235168","doi":"10.1016/j.insmatheco.2015.12.003","title":"Marginal Indemnification Function formulation for optimal reinsurance","year":2015,"lang":"en","type":"article","venue":"Insurance Mathematics and Economics","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":95,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Reinsurance; Function (biology); Mathematics; Mathematical optimization; Actuarial science; Business; Biology","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":[0.00432584,0.001497019,0.00204838,0.001073848,0.0004919188,0.002588402,0.002408371,0.003030132,0.009603976],"category_scores_gemma":[0.007616584,0.001012986,0.001325761,0.0007616775,0.001407239,0.003998073,0.001955174,0.002952884,0.000776303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002125253,"about_ca_system_score_gemma":0.002409488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002195975,"about_ca_topic_score_gemma":0.002202207,"domain_scores_codex":[0.9990488,0.0004696447,0.00003960989,0.0001335109,0.0001965832,0.0001118024],"domain_scores_gemma":[0.9987539,0.0006904583,0.00007644365,0.00008223394,0.0002807474,0.0001162728],"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":[0.00005846025,0.0000772816,0.0004005287,0.0001931793,0.00006342623,0.0001467868,0.0001252476,0.4022755,0.00130027,0.5707119,0.005064942,0.01958246],"study_design_scores_gemma":[0.000009661569,0.00001737806,0.0001486895,0.00003692598,0.00001660411,0.00004199224,0.00002376042,0.9152073,0.0002750115,0.08241485,0.001797387,0.00001044916],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01058299,0.0009183089,0.9738799,0.001637027,0.0001895432,0.00007161228,0.0001229379,0.00007960803,0.01251805],"genre_scores_gemma":[0.6412756,0.002239648,0.2880455,0.0009903685,0.0007465841,0.0006329881,0.0003898364,0.0004442956,0.06523518],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009603976,"threshold_uncertainty_score":0.03212851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1313474261950345,"score_gpt":0.3339147880857693,"score_spread":0.2025673618907348,"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."}}