{"id":"W2119834512","doi":"10.1186/s13012-015-0220-6","title":"A scoping review of classification schemes of interventions to promote and integrate evidence into practice in healthcare","year":2015,"lang":"en","type":"review","venue":"Implementation Science","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McMaster University","funders":"Canadian Institutes of Health Research","keywords":"CINAHL; PsycINFO; Psychological intervention; Grey literature; Knowledge translation; Health informatics; MEDLINE; Public health; Health care; Health services research; Health administration; Nursing research; Medicine; Systematic review; Intervention (counseling); Evidence-based medicine; Data science; Knowledge management; Management science; Computer science; Alternative medicine; Nursing; Political 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03015258,0.0002977557,0.001534004,0.001430212,0.0003811518,0.00003066557,0.0008748706,0.0001153389,0.0001232638],"category_scores_gemma":[0.02939087,0.0002614312,0.0001216385,0.005860317,0.000422168,0.001669316,0.0005431263,0.0005174854,0.00004730915],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001254117,"about_ca_system_score_gemma":0.01699772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001738566,"about_ca_topic_score_gemma":0.001432796,"domain_scores_codex":[0.9887995,0.002870182,0.005211462,0.000859611,0.001536418,0.0007228722],"domain_scores_gemma":[0.9877333,0.00344278,0.00460655,0.000707297,0.003031949,0.0004781233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.000004508351,0.00001677982,0.0001352658,0.4434299,0.000003990001,3.760659e-7,0.004974222,4.008264e-8,0.00001978596,0.001017235,0.0003956314,0.5500023],"study_design_scores_gemma":[0.0002640367,0.0002103156,0.0001216442,0.8244617,0.00009840933,0.00000491892,0.004201971,0.000003280734,0.00001540259,0.00008980552,0.1703247,0.0002038174],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001288446,0.974585,0.0008012064,0.01136478,0.0002845016,0.01262598,0.0001172303,0.00002366225,0.00006880229],"genre_scores_gemma":[0.0002749555,0.9797671,0.01495312,0.002760085,0.00003382561,0.002147502,0.00002650036,0.00002114714,0.00001577446],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.5497985,"threshold_uncertainty_score":0.9999838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9261784750454651,"score_gpt":0.8362171506493193,"score_spread":0.08996132439614579,"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."}}