{"id":"W2904815575","doi":"10.1016/j.gaceta.2018.09.003","title":"Application of two-part models and Cholesky decomposition to incorporate covariate-adjusted utilities in probabilistic cost-effectiveness models","year":2018,"lang":"en","type":"article","venue":"Gaceta Sanitaria","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Cholesky decomposition; Covariate; Minimum degree algorithm; Mathematics; Probabilistic logic; Decomposition; Statistics; Econometrics; Applied mathematics; Incomplete Cholesky factorization; Eigenvalues and eigenvectors; Physics; Chemistry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.008528345,0.0002090441,0.0008633573,0.0003959761,0.000124362,0.00005459303,0.0002066732,0.0001394674,0.00004122841],"category_scores_gemma":[0.000488709,0.000277511,0.00004827908,0.0003498895,0.0001432526,0.0007115614,0.00008589898,0.0001282227,0.0002087984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004746474,"about_ca_system_score_gemma":0.0001146403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00357018,"about_ca_topic_score_gemma":0.001343168,"domain_scores_codex":[0.9962247,0.0004259657,0.002290956,0.0006421349,0.00008647589,0.0003297507],"domain_scores_gemma":[0.9976096,0.0005364811,0.0009998952,0.0005094478,0.0001959797,0.0001486013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002299443,0.0002313173,0.0156386,0.0006661676,0.00005935106,4.799332e-7,0.003909106,0.06892858,0.0001524054,0.909191,0.0003792871,0.0006137453],"study_design_scores_gemma":[0.00144617,0.0001530834,0.0362629,0.0001561479,0.00001246495,0.000003210077,0.0002847229,0.5124123,0.00006443576,0.448537,0.0003653083,0.0003022027],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7787505,0.0002693796,0.214226,0.001229426,0.0002907517,0.002894673,0.000343461,0.00004514564,0.001950693],"genre_scores_gemma":[0.9939181,0.00001727397,0.004406652,0.00074276,0.0001363938,0.0006379364,0.00008218623,0.00003087846,0.00002787884],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.460654,"threshold_uncertainty_score":0.9999677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3937059297906813,"score_gpt":0.4335926947942675,"score_spread":0.03988676500358629,"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."}}