{"id":"W2329615048","doi":"10.1371/journal.pone.0151724","title":"Propensity Score-Based Approaches to Confounding by Indication in Individual Patient Data Meta-Analysis: Non-Standardized Treatment for Multidrug Resistant Tuberculosis","year":2016,"lang":"en","type":"review","venue":"PLoS ONE","topic":"Tuberculosis Research and Epidemiology","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Health and Medical Research Council","keywords":"Propensity score matching; Confounding; Observational study; Medicine; Extensively drug-resistant tuberculosis; Meta-analysis; Tuberculosis; Randomized controlled trial; Internal medicine; Covariate; Intensive care medicine; Mycobacterium tuberculosis; Statistics; Pathology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1487664,0.003237926,0.008966473,0.006826169,0.0007414063,0.00397643,0.003975858,0.003182378,0.003330636],"category_scores_gemma":[0.2290403,0.001668094,0.04361732,0.007918487,0.001354556,0.002411345,0.003147551,0.003514641,0.0002399606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001942404,"about_ca_system_score_gemma":0.002953205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003907901,"about_ca_topic_score_gemma":0.003158979,"domain_scores_codex":[0.6876395,0.2878679,0.01142784,0.007694582,0.004723864,0.0006462865],"domain_scores_gemma":[0.8073381,0.1678845,0.009048535,0.01242611,0.002783494,0.0005193261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.003847553,0.00006248133,0.02006427,0.01478189,0.900638,0.0001825092,0.0001827443,0.02041703,0.0002388282,0.004553696,0.002112033,0.03291897],"study_design_scores_gemma":[0.005402439,0.001013755,0.01819205,0.004136663,0.8066418,0.0003447267,0.0001661753,0.09871383,0.001042781,0.05515983,0.008901495,0.0002844151],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.04923875,0.2721901,0.6590707,0.004841407,0.002626698,0.004840104,0.004430618,0.001170978,0.001590582],"genre_scores_gemma":[0.7358515,0.03095829,0.2154101,0.002613058,0.001034825,0.009864459,0.002796756,0.0003908779,0.001080305],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.1487664,"threshold_uncertainty_score":0.786761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6900798852773894,"score_gpt":0.4231668734159686,"score_spread":0.2669130118614207,"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."}}