{"id":"W1964670877","doi":"10.1016/j.csda.2008.02.034","title":"A random effects four-part model, with application to correlated medical costs","year":2008,"lang":"en","type":"article","venue":"Computational Statistics & Data Analysis","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"University of Virginia; Agency for Healthcare Research and Quality; Ryerson University","keywords":"Random effects model; Mathematics; Statistics; Laplace's method; Applied mathematics; Generalized estimating equation; Mixed model; Generalized linear model; Generalized linear mixed model; Multivariate statistics; Linear model; Laplace transform; Econometrics; Medicine; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006740235,0.0002511928,0.0006493581,0.0002469936,0.0002681308,0.0000544017,0.0005736261,0.00009976169,0.0002234117],"category_scores_gemma":[0.004109351,0.0002094537,0.00005702575,0.001298805,0.000174635,0.0001077467,0.000219662,0.0002252756,0.00008020917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000858697,"about_ca_system_score_gemma":0.0002834271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000153655,"about_ca_topic_score_gemma":0.0002363213,"domain_scores_codex":[0.9969023,0.0002462619,0.0006024285,0.0006808423,0.001268296,0.0002998745],"domain_scores_gemma":[0.9919094,0.006226509,0.0002198651,0.0007762923,0.0004468002,0.00042109],"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":[0.0005097383,0.0006011173,0.004864269,0.0001699638,0.003089141,0.0004344,0.0003172263,0.09580404,0.000006763926,0.7527063,0.0722169,0.0692801],"study_design_scores_gemma":[0.000843377,0.0000584397,0.003060051,0.0000345795,0.001160979,0.00002753038,0.000002773082,0.8156425,0.00000177965,0.1787845,0.0001514854,0.0002319756],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009425684,0.00001415783,0.9951265,0.0002067305,0.00003907429,0.0004172997,0.00299358,0.00008003299,0.0001800654],"genre_scores_gemma":[0.07414556,0.00001726285,0.9212666,0.0002917856,0.00005301642,0.00006610318,0.004077234,0.00002670032,0.00005572744],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7198384,"threshold_uncertainty_score":0.8541274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06068986729945356,"score_gpt":0.3676426477605897,"score_spread":0.3069527804611361,"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."}}