{"id":"W2117085209","doi":"10.1503/cmaj.131353","title":"Randomized trials with missing outcome data: how to analyze and what to report","year":2014,"lang":"en","type":"review","venue":"Canadian Medical Association Journal","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":110,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Randomized controlled trial; Baseline (sea); Outcome (game theory); Random assignment; Missing data; Computer science; Gold standard (test); Medicine; Surgery; Internal medicine; Machine learning; Pathology; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2840629,0.006555163,0.04000041,0.009086565,0.002932717,0.01271825,0.006192157,0.01655211,0.01112274],"category_scores_gemma":[0.6855491,0.004998641,0.02604468,0.009042393,0.0067603,0.01583232,0.003485689,0.01229296,0.003791312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005618307,"about_ca_system_score_gemma":0.01731499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004503584,"about_ca_topic_score_gemma":0.006796659,"domain_scores_codex":[0.519003,0.3494706,0.09029885,0.01074809,0.02874262,0.001736785],"domain_scores_gemma":[0.2346285,0.6647576,0.04561078,0.02905055,0.02326742,0.002685236],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.005112562,0.0003342807,0.004908145,0.6233183,0.05609364,0.0003638493,0.001003283,0.00374614,0.0005647162,0.01911501,0.08895139,0.1964887],"study_design_scores_gemma":[0.02145135,0.002168558,0.006528419,0.4912721,0.1120689,0.0008061156,0.001072848,0.01328111,0.002509415,0.2104242,0.1370563,0.001360672],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.005615405,0.5319347,0.1768788,0.1422074,0.04324849,0.06973347,0.02330381,0.002151308,0.004926596],"genre_scores_gemma":[0.07641281,0.1677606,0.4703215,0.0570761,0.01849511,0.200047,0.006437372,0.001214633,0.002234919],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7159371,"threshold_uncertainty_score":0.8828779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.71926205492112,"score_gpt":0.5635865404804616,"score_spread":0.1556755144406584,"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."}}