{"id":"W4280542190","doi":"10.1002/pst.2234","title":"Standard and reference‐based conditional mean imputation","year":2022,"lang":"en","type":"article","venue":"Pharmaceutical Statistics","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; Medical Research Council Canada","keywords":"Missing data; Jackknife resampling; Frequentist inference; Imputation (statistics); Pooling; Computer science; Statistics; Inference; Bayesian probability; Econometrics; Bayesian inference; Mathematics; Estimator; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002377775,0.0002053739,0.000439348,0.00007267571,0.0004041483,0.00005589055,0.0001862883,0.00006187963,0.007100018],"category_scores_gemma":[0.01472986,0.0002041113,0.00004577581,0.0001912638,0.0003269003,0.00004239453,0.0002060868,0.0006723935,0.0000204555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001627459,"about_ca_system_score_gemma":0.0001331246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004413636,"about_ca_topic_score_gemma":0.000002018378,"domain_scores_codex":[0.9963514,0.001181323,0.0007319804,0.0004169096,0.0009426817,0.0003757357],"domain_scores_gemma":[0.9646532,0.03448611,0.0001905149,0.0001892673,0.0001648313,0.0003161095],"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":[0.0004635285,0.0001951652,0.0002307217,0.0001200868,0.00005617508,0.00005639077,0.00005571207,0.00007420139,0.00009741197,0.958324,0.01339494,0.02693174],"study_design_scores_gemma":[0.002016998,0.0003287974,0.0003030619,0.000006778095,0.0001713026,0.00001418226,0.00004750125,0.02586359,0.0002853734,0.9508915,0.01982024,0.0002506862],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002581211,0.00003776214,0.9832269,0.0007958927,0.0003715942,0.0004619886,0.01118767,0.000127627,0.001209377],"genre_scores_gemma":[0.2238766,0.00001341191,0.774563,0.001114018,0.0001013494,0.0001081094,0.0001196899,0.00003546109,0.00006839646],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2212954,"threshold_uncertainty_score":0.9938076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6731853966455711,"score_gpt":0.6174407262752281,"score_spread":0.05574467037034303,"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."}}