{"id":"W10119467","doi":"","title":"Using DIC to compare selection models with non-ignorable missing responses","year":2010,"lang":"en","type":"article","venue":"","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Missing data; Model selection; Computer science; Statistics; Econometrics; Bayesian probability; Data mining; Artificial intelligence; Mathematics; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002943493,0.0001146571,0.0001912116,0.00007236385,0.0001606734,0.00008861769,0.00008152289,0.00003377279,0.0002671649],"category_scores_gemma":[0.0004188048,0.00008259351,0.00001803384,0.0002279807,0.00003614977,0.0001107759,0.00002315109,0.0001694302,0.000008701692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002089638,"about_ca_system_score_gemma":0.00007911434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001565805,"about_ca_topic_score_gemma":0.0002035564,"domain_scores_codex":[0.9992046,0.00006063675,0.0001658073,0.0001935148,0.0001598158,0.0002155618],"domain_scores_gemma":[0.9988593,0.0006704141,0.00004539728,0.0001695341,0.0001250512,0.0001302859],"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":[0.0003084049,0.0001534292,0.00204987,0.000119058,0.00002891283,0.00001245856,0.0005517332,0.0001852757,0.1136896,0.8610896,0.001274923,0.02053665],"study_design_scores_gemma":[0.0001913004,0.00007955744,0.0003854096,0.00009223862,0.00003209112,0.00003863695,0.00007417791,0.204221,0.01519003,0.7794195,0.000069807,0.0002062678],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1190428,9.299982e-7,0.8736677,0.0001040147,0.00005133477,0.0001477503,0.000004059759,0.00006432541,0.006917185],"genre_scores_gemma":[0.3885335,8.605956e-8,0.6111615,0.00006169738,0.00002844328,0.00000389974,2.326615e-7,0.0000119679,0.0001986993],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2694907,"threshold_uncertainty_score":0.3368066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1774432488167736,"score_gpt":0.4273438123093972,"score_spread":0.2499005634926237,"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."}}