{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005752004,0.0001060483,0.0002020542,0.00006359075,0.0001161664,0.00006183215,0.0003365201,0.00005845176,0.0001045119],"category_scores_gemma":[0.001460861,0.00008893077,0.00003995165,0.0002029022,0.00003011321,0.0001324336,0.000226222,0.0001230928,0.00002698174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001937668,"about_ca_system_score_gemma":0.00006228663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006898024,"about_ca_topic_score_gemma":9.606659e-7,"domain_scores_codex":[0.9988348,0.00006340285,0.0002382995,0.0003093482,0.0001859831,0.0003681523],"domain_scores_gemma":[0.9978763,0.001413391,0.00005586146,0.0005103271,0.00004926656,0.00009479402],"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":[0.00002668942,0.00003590952,0.00001820948,0.00009172017,0.00001859201,0.000005832437,0.00009620116,0.000006971491,0.001242658,0.9799946,0.005062941,0.01339968],"study_design_scores_gemma":[0.0001977424,0.00001732828,0.000007403413,0.00002379596,0.00001908018,0.000001428596,0.00001912512,0.452079,0.0001888486,0.5471423,0.0002363972,0.00006757812],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003345086,0.00001207248,0.9948993,0.0002492295,0.0002019519,0.0003443419,0.0004108975,0.0001615457,0.0003755875],"genre_scores_gemma":[0.01697743,0.000005097953,0.9824802,0.00004304435,0.000276014,0.00003013833,0.00008188649,0.00002921291,0.00007697655],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.452072,"threshold_uncertainty_score":0.3626491,"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."}}