{"id":"W2136991564","doi":"10.1136/bmjopen-2015-009368","title":"Reporting, handling and assessing the risk of bias associated with missing participant data in systematic reviews: a methodological survey","year":2015,"lang":"en","type":"article","venue":"BMJ Open","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto; McMaster University","funders":"Gottfried und Julia Bangerter-Rhyner-Stiftung; Instituto de Salud Carlos III; Canadian Institutes of Health Research; Suomen Lääketieteen Säätiö; Suomen Kulttuurirahasto; Sigrid Juséliuksen Säätiö; Jane ja Aatos Erkon Säätiö","keywords":"Medicine; Missing data; Systematic review; Meta-analysis; MEDLINE; Reporting bias; Publication bias; Cochrane Library; Relative risk; Confidence interval; Statistics; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.9022187,0.0002328594,0.007773139,0.0001218644,0.0001453984,0.002429062,0.003067845,0.00007058555,0.0000943288],"category_scores_gemma":[0.9356282,0.00007323608,0.0002643855,0.001532418,0.00009803801,0.0005674837,0.001256809,0.0001935151,0.00002887634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002189108,"about_ca_system_score_gemma":0.000279986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007676735,"about_ca_topic_score_gemma":0.001839107,"domain_scores_codex":[0.6413418,0.3186092,0.03315519,0.001469265,0.005016686,0.000407787],"domain_scores_gemma":[0.4451942,0.2885164,0.2335271,0.02748264,0.004559642,0.0007199679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001580798,0.0000495417,0.9926345,0.001119976,0.0003380041,0.00001929244,0.001468433,0.00009804972,0.000006301466,0.00002203206,0.002548845,0.001679155],"study_design_scores_gemma":[0.0007375778,0.0001033012,0.8481807,0.02346992,0.002555439,0.00008726228,0.007468685,0.1139536,0.000009098467,0.002354472,0.0006676131,0.0004123832],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9260837,0.008419842,0.03937971,0.0006204009,0.0001629095,0.0233004,0.00003686809,0.000006631031,0.001989484],"genre_scores_gemma":[0.9695107,0.00003251759,0.02935065,0.0001066253,0.00001848684,0.0003521911,0.00001908584,0.00001229975,0.0005973927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2003719,"threshold_uncertainty_score":0.9986065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9942439294609863,"score_gpt":0.7377356540891176,"score_spread":0.2565082753718687,"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."}}