{"id":"W4386168039","doi":"10.3390/e25091262","title":"Profile Likelihood for Hierarchical Models Using Data Doubling","year":2023,"lang":"en","type":"article","venue":"Entropy","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Likelihood function; Mathematics; Frequentist inference; Statistical inference; Marginal likelihood; Estimation theory; Algorithm; Applied mathematics; Mixture model; Estimator; Statistical model; Bayesian inference; Computer science; Bayesian probability; Statistics","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":[0.01591158,0.0009037369,0.001436641,0.00283958,0.001044986,0.002285047,0.003069761,0.001615199,0.004048362],"category_scores_gemma":[0.06254125,0.0008723955,0.001816366,0.002145886,0.003440039,0.005282376,0.005091959,0.003946385,0.001113074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002434901,"about_ca_system_score_gemma":0.002507661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00334677,"about_ca_topic_score_gemma":0.002767666,"domain_scores_codex":[0.994799,0.003029836,0.0002622718,0.0006805325,0.000977568,0.0002507379],"domain_scores_gemma":[0.974133,0.02067505,0.001287913,0.002434427,0.001032423,0.000437078],"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":[0.00005246949,0.00002718338,0.001201577,0.0001542514,0.00003707309,0.0001853372,0.0002701747,0.127297,0.0009192928,0.8393155,0.00163826,0.02890188],"study_design_scores_gemma":[0.000009732356,0.00001062271,0.0002591258,0.00002404388,0.000006800444,0.00008151989,0.00003205721,0.4513721,0.0003779572,0.5463423,0.001464533,0.00001921574],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00338011,0.00009364763,0.9953133,0.0001737846,0.00000911508,0.0000353428,0.0001080522,0.00009504728,0.0007914986],"genre_scores_gemma":[0.2543418,0.0007741333,0.7367321,0.0004757581,0.0001685449,0.0008277562,0.001261857,0.0004421745,0.00497591],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01591158,"threshold_uncertainty_score":0.08414948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3277383071030227,"score_gpt":0.4544069157570721,"score_spread":0.1266686086540494,"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."}}