{"id":"W1873375728","doi":"10.1002/sim.6314","title":"EM for regularized zero‐inflated regression models with applications to postoperative morbidity after cardiac surgery in children","year":2014,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; Montreal Children's Hospital","funders":"National Center for Advancing Translational Sciences; National Institute of Environmental Health Sciences; National Heart, Lung, and Blood Institute; National Institute of Diabetes and Digestive and Kidney Diseases; National Cancer Institute; National Institutes of Health; Charles H. Hood Foundation","keywords":"Poisson regression; Count data; Poisson distribution; Expectation–maximization algorithm; Regression; Medicine; Likelihood function; Statistics; Overdispersion; Regression analysis; Zero-inflated model; Cardiac surgery; Model selection; Computer science; Econometrics; Mathematics; Maximum likelihood; Surgery; Population","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":[],"consensus_categories":[],"category_scores_codex":[0.001534059,0.0002205599,0.0007448362,0.0001990489,0.00005412223,0.00001418592,0.0001230491,0.0000963821,0.00005165258],"category_scores_gemma":[0.003998294,0.0001521262,0.00002577563,0.0003555766,0.0001273315,0.00004296303,0.00003884924,0.0002229665,0.000003390687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007170808,"about_ca_system_score_gemma":0.00006158851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001514987,"about_ca_topic_score_gemma":0.0001235799,"domain_scores_codex":[0.9981319,0.0002927885,0.0005690588,0.0003823494,0.0003116053,0.0003122892],"domain_scores_gemma":[0.9947004,0.004376033,0.0001247657,0.0003977416,0.0002532627,0.0001477629],"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":[0.0007801951,0.0001956775,0.01224247,0.0002221578,0.00007055104,0.00001040809,0.002637976,0.0001008561,0.0003731939,0.9139463,0.0127705,0.05664973],"study_design_scores_gemma":[0.001150684,0.0003285952,0.04041059,0.0006796398,0.0000779965,0.000003241342,0.0001286348,0.01629414,0.0001396742,0.9402565,0.0002020835,0.0003282031],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03459457,0.00003044283,0.9626361,0.0003080297,0.00006958315,0.001475736,0.0006275983,0.0000268819,0.0002310593],"genre_scores_gemma":[0.288027,0.00001973411,0.7105826,0.0002365208,0.00007606776,0.000803457,0.0001331215,0.00003162854,0.00008993972],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2534324,"threshold_uncertainty_score":0.6203528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05210787311159458,"score_gpt":0.3740036816381332,"score_spread":0.3218958085265386,"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."}}