{"id":"W2604568423","doi":"10.1002/jrsm.1287","title":"Machine learning for identifying Randomized Controlled Trials: An evaluation and practitioner's guide","year":2018,"lang":"en","type":"article","venue":"Research Synthesis Methods","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":449,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. National Library of Medicine; Agency for Healthcare Research and Quality; National Institutes of Health; National Cancer Institute; Medical Research Council; McMaster University","keywords":"Computer science; Machine learning; Artificial intelligence; Randomized controlled trial; Workflow; Convolutional neural network; Support vector machine; Systematic review; Sensitivity (control systems); Data mining; MEDLINE; Medicine; Database","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4261457634092655,"score_gpt":0.6226321823758852,"score_spread":0.1964864189666198,"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."}}