{"id":"W6920668901","doi":"10.6084/m9.figshare.14516296","title":"Additional file 2 of Dynamic model updating (DMU) approach for statistical learning model building with missing data","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Missing data; Table (database); Model building; Statistical model; Regression analysis; Data modeling","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":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008663403,0.0001494403,0.0002825478,0.00003056517,0.0001450311,0.00006140461,0.0002462429,0.00007349978,0.7175965],"category_scores_gemma":[0.03792239,0.0001355996,0.00003326452,0.0001129318,0.00001889046,0.0001341722,0.0002197095,0.0002258202,0.000009606275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002867282,"about_ca_system_score_gemma":0.0003561096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.901099e-7,"about_ca_topic_score_gemma":0.000001134213,"domain_scores_codex":[0.998721,0.00006290257,0.0002926975,0.0004157899,0.0002551178,0.0002524803],"domain_scores_gemma":[0.9899842,0.009121426,0.0001940095,0.0003559687,0.0002600307,0.00008438223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001256617,0.00006365689,1.24077e-7,0.0008702585,0.00002638878,0.000005731936,0.0000289969,0.001756457,0.00003755673,0.0155978,0.9651731,0.01642733],"study_design_scores_gemma":[0.0001299226,0.00002080629,0.000003883544,0.001719888,0.000023791,0.00001231844,0.00005561701,0.8999221,0.00001892024,0.09630846,0.001620505,0.0001637786],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[2.751265e-7,0.000003249877,0.4955073,0.000004549824,0.000001245683,0.00006861242,0.5032339,0.0000208419,0.001160018],"genre_scores_gemma":[0.0001062198,6.934535e-8,0.5191031,0.00001273226,0.00001360377,0.0001452697,0.4804988,0.00002051589,0.00009973603],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9635527,"threshold_uncertainty_score":0.9701816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1768662781369223,"score_gpt":0.3901808655635539,"score_spread":0.2133145874266316,"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."}}