{"id":"W3165135368","doi":"10.1186/s13643-021-01700-x","title":"Text mining to support abstract screening for knowledge syntheses: a semi-automated workflow","year":2021,"lang":"en","type":"article","venue":"Systematic Reviews","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Work & Health; University of Toronto; Queen's University; Toronto Metropolitan University; St. Michael's Hospital","funders":"University of Toronto; Canada Excellence Research Chairs, Government of Canada; Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Research, Innovation and Science; Canada Research Chairs","keywords":"Medicine; Workflow; Data science; Knowledge management; Database","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":["metaresearch"],"category_scores_codex":[0.2433764,0.006254593,0.008086931,0.03388676,0.003826281,0.01248958,0.008006644,0.002707408,0.02345427],"category_scores_gemma":[0.4362323,0.004520275,0.01100067,0.02070595,0.002584398,0.00824888,0.01182397,0.005394165,0.01278166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005756501,"about_ca_system_score_gemma":0.05501957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006879688,"about_ca_topic_score_gemma":0.01424019,"domain_scores_codex":[0.8173829,0.101116,0.05187616,0.0128729,0.0156672,0.001084768],"domain_scores_gemma":[0.30209,0.5405509,0.05102014,0.04051524,0.06143387,0.00438988],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001727142,0.0004763988,0.003776459,0.05976183,0.002548488,0.0006430416,0.007657609,0.006642772,0.01178839,0.006535898,0.08865291,0.8097889],"study_design_scores_gemma":[0.008872794,0.001895222,0.01914676,0.04322047,0.007682575,0.002515259,0.01004277,0.1932839,0.05842206,0.1938668,0.4576713,0.003380157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006703652,0.005304358,0.8607082,0.007313426,0.0009320999,0.03876471,0.0314798,0.04532037,0.003473426],"genre_scores_gemma":[0.008287153,0.000856146,0.9716781,0.0003903072,0.0001925426,0.0121913,0.00519283,0.0006995554,0.0005120292],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7566236,"threshold_uncertainty_score":0.9330516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7216169933901161,"score_gpt":0.5341331498802864,"score_spread":0.1874838435098297,"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."}}