{"id":"W2294602088","doi":"10.1016/j.jclinepi.2016.03.004","title":"Complementary approaches to searching MEDLINE may be sufficient for updating systematic reviews","year":2016,"lang":"en","type":"article","venue":"Journal of Clinical Epidemiology","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada; Canadian Patient Safety Institute; Children's Hospital of Eastern Ontario","funders":"Agency for Healthcare Research and Quality; U.S. Department of Health and Human Services","keywords":"MEDLINE; Precision and recall; Ranking (information retrieval); Recall; Computer science; Support vector machine; Systematic review; Medicine; Information retrieval; Machine learning; Data mining; Psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["metaresearch"],"domain":"methods","study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"gpt","categories":["metaresearch"],"domain":"methods","study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_broad","insufficient_payload"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.8567015,0.0003393521,0.02210263,0.0004312005,0.0001395373,0.00009265075,0.002753133,0.0001595202,0.001795051],"category_scores_gemma":[0.8972092,0.0001102647,0.007389304,0.0005186656,0.0001466952,0.0001886422,0.0002842229,0.0004131786,0.000594911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005652155,"about_ca_system_score_gemma":0.0001299055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003017065,"about_ca_topic_score_gemma":0.00001522345,"domain_scores_codex":[0.5571618,0.2895389,0.1462968,0.001666699,0.004310707,0.001025104],"domain_scores_gemma":[0.1725729,0.7444598,0.07617056,0.003762218,0.001886625,0.001147928],"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":[0.0002273316,0.0004860232,0.1917595,0.006449413,0.001560733,0.00001294804,0.0005722911,0.000604764,0.00005619962,0.05625773,0.6241851,0.1178279],"study_design_scores_gemma":[0.002894954,0.002753449,0.02040586,0.01128979,0.002008975,0.0002916293,0.002654216,0.02667669,0.00001354057,0.0672197,0.863032,0.0007592334],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0573298,0.002053797,0.8157516,0.1196776,0.00152862,0.00311096,0.00003124567,0.000003293263,0.0005131418],"genre_scores_gemma":[0.4920712,0.0005546715,0.4806899,0.02095932,0.002419847,0.0001646325,0.000007014392,0.00003691395,0.003096469],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.454921,"threshold_uncertainty_score":0.9991174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9829686983659722,"score_gpt":0.7045193499622208,"score_spread":0.2784493484037515,"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."}}