{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001657842,0.00007213518,0.0001072411,0.00002042735,0.00007781338,0.00006421307,0.00004147341,0.00004485267,0.00001235186],"category_scores_gemma":[0.001508105,0.00005356872,0.000003903118,0.0000328501,0.00001619104,0.0001505544,0.00003459156,0.00004984377,5.217086e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002669669,"about_ca_system_score_gemma":0.00001557426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003083077,"about_ca_topic_score_gemma":0.000052503,"domain_scores_codex":[0.9994876,0.00003343999,0.0001097614,0.0001653739,0.00009820212,0.0001055728],"domain_scores_gemma":[0.998314,0.001352961,0.00008293929,0.0001104289,0.0001019788,0.00003763989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004373102,0.0001556901,0.001892104,0.001438445,0.0002684409,0.000002653659,0.004388357,0.01804296,0.004788069,0.1829511,0.01357032,0.7720646],"study_design_scores_gemma":[0.0002007898,0.00009228219,0.0002250877,0.000008777625,0.00002757335,0.000001927055,0.00004083907,0.6744658,0.00004413936,0.3248325,0.000007849108,0.00005239997],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2184177,0.000009933855,0.7809459,0.0001036754,0.0000146163,0.0003244673,0.0001153063,0.00002479609,0.00004354925],"genre_scores_gemma":[0.4221447,0.000004309873,0.5777,0.00002214657,0.000009844091,0.00001118609,0.00002500996,0.000007009794,0.00007584833],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7720122,"threshold_uncertainty_score":0.2184469,"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."}}