{"id":"W1561370587","doi":"10.18438/b82p55","title":"The Contributions of MEDLINE, Other Bibliographic Databases and Various Search Techniques to NICE Public Health Guidance","year":2015,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nice; MEDLINE; Grey literature; Systematic review; Excellence; Medicine; Database; Public health; Cochrane Library; Multidisciplinary approach; Information retrieval; Computer science; Political science; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.4789565,0.003479986,0.01483837,0.1165998,0.002009517,0.02571339,0.006910766,0.006969707,0.01081393],"category_scores_gemma":[0.8573957,0.004442964,0.01192343,0.09347117,0.003826811,0.01859699,0.01129902,0.004863231,0.003097658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01555181,"about_ca_system_score_gemma":0.04959808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01105469,"about_ca_topic_score_gemma":0.02795391,"domain_scores_codex":[0.266817,0.4303008,0.227979,0.006280071,0.06623553,0.002387671],"domain_scores_gemma":[0.04890383,0.8227147,0.05620971,0.01460323,0.055972,0.001596568],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"systematic_review","study_design_gemma":"observational","study_design_scores_codex":[0.0009190594,0.0000635272,0.004926432,0.6143203,0.008231402,0.0004229493,0.003948129,0.0008087005,0.000618896,0.004958051,0.04282896,0.3179535],"study_design_scores_gemma":[0.0004916401,0.0002664839,0.005656495,0.8889574,0.01482106,0.0005553037,0.002054112,0.001082754,0.0005755259,0.006214723,0.07910049,0.0002239754],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.005285712,0.8034383,0.0309826,0.1182976,0.005835184,0.009290069,0.01063884,0.001033845,0.01519783],"genre_scores_gemma":[0.05614649,0.6306422,0.2460323,0.02808548,0.00402113,0.02574845,0.007190543,0.0006372965,0.001496119],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9742866,"threshold_uncertainty_score":0.6425395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.399912879765864,"score_gpt":0.5858722331311372,"score_spread":0.1859593533652732,"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."}}