{"id":"W2129163850","doi":"10.1001/jama.2014.5559","title":"How to Read a Systematic Review and Meta-analysis and Apply the Results to Patient Care","year":2014,"lang":"en","type":"review","venue":"JAMA","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":451,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Population Health Research Institute; McMaster University","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Credibility; Meta-analysis; Consistency (knowledge bases); Confidence interval; MEDLINE; Publication bias; Evidence-based medicine; Systematic review; Quality (philosophy); Quality of evidence; Alternative medicine; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1761826,0.003590717,0.01678596,0.01951757,0.002671462,0.01830172,0.007697097,0.02068304,0.02489171],"category_scores_gemma":[0.655488,0.005762385,0.008400412,0.01070318,0.005689987,0.02525196,0.006344703,0.01943347,0.01722015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006368454,"about_ca_system_score_gemma":0.03582995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007896929,"about_ca_topic_score_gemma":0.01377866,"domain_scores_codex":[0.8275567,0.09797896,0.03897484,0.004808024,0.02928964,0.001391841],"domain_scores_gemma":[0.4595282,0.3329593,0.05449185,0.02400783,0.1164251,0.01258766],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001063371,0.0002837714,0.001198336,0.1022216,0.00564156,0.0006970368,0.00278823,0.001107314,0.001275244,0.009039698,0.6236616,0.2510223],"study_design_scores_gemma":[0.005692326,0.000578534,0.004874852,0.2189169,0.008919279,0.001250717,0.003004568,0.00653083,0.002252368,0.1819762,0.5645288,0.001474637],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.001559867,0.1341639,0.05939896,0.6353749,0.1397748,0.01451411,0.005371912,0.002569993,0.007271493],"genre_scores_gemma":[0.02169232,0.1650557,0.4842412,0.2006086,0.08770709,0.0267017,0.002456239,0.002084905,0.009452174],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8238174,"threshold_uncertainty_score":0.9317538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6301240771174976,"score_gpt":0.5044127862148174,"score_spread":0.1257112909026802,"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."}}