{"id":"W2964291876","doi":"10.1002/sta4.21","title":"Simultaneous model selection and estimation for mean and association structures with clustered binary data","year":2013,"lang":"en","type":"article","venue":"Stat","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; York University","funders":"National Science Council","keywords":"Estimator; Mathematics; Covariate; Model selection; Applied mathematics; Oracle; Mathematical optimization; Selection (genetic algorithm); Feature selection; Estimating equations; Mean squared error; Binary number; Statistics; Computer science; Artificial intelligence","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":[0.02316836,0.001602985,0.002577156,0.002019686,0.0007884132,0.001668515,0.002966732,0.001571608,0.00192612],"category_scores_gemma":[0.08925252,0.001517688,0.002512479,0.00223064,0.001690852,0.002113206,0.003029977,0.003729232,0.000546651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00102293,"about_ca_system_score_gemma":0.002990276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003740291,"about_ca_topic_score_gemma":0.004819424,"domain_scores_codex":[0.9774344,0.01802802,0.0006100511,0.00218176,0.001373942,0.0003717449],"domain_scores_gemma":[0.9333652,0.05767664,0.003192376,0.003603294,0.001799079,0.0003634267],"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":[0.0003727731,0.0002404929,0.01969467,0.0006062288,0.001702133,0.0005381451,0.0007214919,0.5422478,0.00298424,0.1843113,0.003743567,0.2428372],"study_design_scores_gemma":[0.00005510763,0.00009910741,0.002215211,0.00003892871,0.00009732573,0.0001133488,0.00003417048,0.9296228,0.0009364233,0.06531082,0.001436952,0.00003983908],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004022399,0.00008188777,0.9955545,0.0000932885,0.000008197453,0.00004166251,0.00003542197,0.0000784555,0.00008430012],"genre_scores_gemma":[0.134172,0.0003202288,0.8627937,0.0001756467,0.00007345795,0.0006623301,0.0005497899,0.0001209953,0.001131767],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02316836,"threshold_uncertainty_score":0.1225275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08105860480608996,"score_gpt":0.3705794344871222,"score_spread":0.2895208296810323,"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."}}