{"id":"W2024005323","doi":"10.1016/j.mcm.2005.12.011","title":"A two-stage DEA model to evaluate the overall performance of Canadian life and health insurance companies","year":2006,"lang":"en","type":"article","venue":"Mathematical and Computer Modelling","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":152,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Stage (stratigraphy); Life insurance; Actuarial science; Computer science; Health insurance; Econometrics; Business; Operations management; Statistics; Operations research; Mathematics; Economics; Health care; Economic growth","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002473029,0.001215076,0.001500297,0.00103813,0.001435041,0.002323356,0.002358299,0.002545633,0.003646655],"category_scores_gemma":[0.005354688,0.000631895,0.0009491642,0.0009463937,0.001045842,0.0009829224,0.0008034314,0.001728693,0.0003128144],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0113617,"about_ca_system_score_gemma":0.006969318,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7956452,"about_ca_topic_score_gemma":0.6463349,"domain_scores_codex":[0.9992872,0.0001648923,0.00002490752,0.000132503,0.0001024246,0.0002881356],"domain_scores_gemma":[0.9973258,0.001403157,0.0002135261,0.00008498179,0.0007304433,0.0002420906],"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":[0.0002597611,0.00006328311,0.004194558,0.0000284521,0.00006263692,0.0000968267,0.00006096188,0.9837469,0.00043971,0.006954839,0.001087551,0.003004482],"study_design_scores_gemma":[0.00002551707,0.00002652891,0.001523983,0.000003328614,0.0000261273,0.000007972999,0.00003349349,0.9971399,0.00009388887,0.0007626733,0.0003413995,0.00001527416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9144763,0.001375366,0.05964764,0.002581126,0.000170992,0.0002328565,0.003911705,0.0003587818,0.01724517],"genre_scores_gemma":[0.984724,0.0002152187,0.004145702,0.00006647228,0.00002259553,0.00007146843,0.0008469459,0.00002157267,0.009886049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9886383,"threshold_uncertainty_score":0.4111166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07062043071787692,"score_gpt":0.2360531918265307,"score_spread":0.1654327611086537,"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."}}