{"id":"W2768527379","doi":"10.1016/j.jclinepi.2017.01.015","title":"GRADE equity guidelines 3: considering health equity in GRADE guideline development: rating the certainty of synthesized evidence","year":2017,"lang":"en","type":"article","venue":"Journal of Clinical Epidemiology","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; McMaster University; Health Sciences Centre; University of Calgary; Impact; Bruyère; University of Ottawa","funders":"National Health and Medical Research Council; U.S. Department of Veterans Affairs; Regeneron Pharmaceuticals; Allergan; Parker Institute for Cancer Immunotherapy; World Health Organization; Medical Research Council; University of Ottawa","keywords":"Guideline; Equity (law); Grading (engineering); Health equity; Actuarial science; Disadvantaged; Evidence-based medicine; Medicine; Psychology; MEDLINE; Public health; Business; Political science; Nursing; Economics; Economic growth","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"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.5041509,0.0002626466,0.005926284,0.0002465366,0.0004601436,0.00004743197,0.00161268,0.000435896,0.00009160902],"category_scores_gemma":[0.7470472,0.0002171076,0.0006126759,0.00009833254,0.0005796601,0.000482397,0.0006467287,0.001327636,0.00004471146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000483765,"about_ca_system_score_gemma":0.001843436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00174381,"about_ca_topic_score_gemma":0.001140178,"domain_scores_codex":[0.9246636,0.009758681,0.06347736,0.0007619319,0.0002949891,0.001043445],"domain_scores_gemma":[0.7912219,0.1268683,0.07900248,0.001601388,0.0007062573,0.0005997084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002140543,0.0002822086,0.8249822,0.0007306912,0.0002848008,0.0000101182,0.000953263,0.002902315,0.000008916023,0.07946045,0.0541045,0.03606651],"study_design_scores_gemma":[0.00310384,0.0004596725,0.6683611,0.003122616,0.00002536952,0.00008250494,0.0007086226,0.01823837,0.00002422161,0.2632913,0.04209447,0.0004878339],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2290836,0.01007689,0.02495085,0.732434,0.00236442,0.0005921726,0.00002274044,0.00001338014,0.000461889],"genre_scores_gemma":[0.8280665,0.003217899,0.1070789,0.06030941,0.001243724,0.00001508642,0.000002374034,0.00002521295,0.00004089667],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6721246,"threshold_uncertainty_score":0.885339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9503496834351777,"score_gpt":0.7147137828651461,"score_spread":0.2356359005700316,"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."}}