{"id":"W2155839122","doi":"10.1177/0962280214568110","title":"Bayesian regression models for the estimation of net cost of disease using aggregate data","year":2015,"lang":"en","type":"article","venue":"Statistical Methods in Medical Research","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Toronto General Hospital; Public Health Ontario; University of Toronto","funders":"","keywords":"Heteroscedasticity; Aggregate (composite); Econometrics; Computer science; Bayesian probability; Skewness; Linear regression; Bayesian linear regression; Linear model; Estimation; Regression; Statistics; Bayesian inference; Data mining; Mathematics; Machine learning; Artificial intelligence; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0197245,0.001433303,0.002351766,0.003200077,0.0004590722,0.002354233,0.003492381,0.001791225,0.005182662],"category_scores_gemma":[0.06428032,0.001313801,0.002369776,0.00314936,0.00112382,0.003754581,0.001415542,0.002792566,0.001146537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001970349,"about_ca_system_score_gemma":0.001394865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01161621,"about_ca_topic_score_gemma":0.01101856,"domain_scores_codex":[0.9904457,0.007164388,0.0003472031,0.0008265304,0.0009289232,0.0002870887],"domain_scores_gemma":[0.9694875,0.0254944,0.002467299,0.001107213,0.001244817,0.0001986709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001894889,0.0001021498,0.005767492,0.000207146,0.0005140195,0.0001094009,0.0002195146,0.7063346,0.0003611416,0.215183,0.002350161,0.068662],"study_design_scores_gemma":[0.00003593844,0.00005488399,0.001660377,0.00008240839,0.00008801121,0.00004853316,0.00003745977,0.8874449,0.0001518584,0.1085628,0.001789242,0.00004354549],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01118687,0.0006143206,0.986048,0.0004651126,0.00003149633,0.0000987544,0.0003927039,0.0001664685,0.0009963227],"genre_scores_gemma":[0.4245124,0.004087593,0.5546545,0.0005451063,0.0002978874,0.001988475,0.002905149,0.0003221304,0.01068673],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0197245,"threshold_uncertainty_score":0.1043144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8612777946749054,"score_gpt":0.7029062873227251,"score_spread":0.1583715073521803,"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."}}