{"id":"W3010352759","doi":"10.1016/j.jclinepi.2020.01.026","title":"Guideline developers in the United States were inconsistent in applying criteria for appropriate Grading of Recommendations, Assessment, Development and Evaluation use","year":2020,"lang":"en","type":"article","venue":"Journal of Clinical Epidemiology","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University; Impact","funders":"","keywords":"Guideline; Grading (engineering); Medicine; Certainty; Family medicine; MEDLINE; Evidence-based medicine; Actuarial science; Alternative medicine; Political science; Pathology; Business; Engineering; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.3905407,0.0006105719,0.001760858,0.0141742,0.003724227,0.01124978,0.003937081,0.004046165,0.001250738],"category_scores_gemma":[0.7816386,0.001738715,0.002588869,0.01090151,0.003361538,0.005740982,0.007191966,0.007094554,0.0003395864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01320052,"about_ca_system_score_gemma":0.05496408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06041708,"about_ca_topic_score_gemma":0.1363529,"domain_scores_codex":[0.5928262,0.1774779,0.1432027,0.009436609,0.07095105,0.006105416],"domain_scores_gemma":[0.1939421,0.4224271,0.07220531,0.02577301,0.2781624,0.007490162],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005973469,0.0006016981,0.2856971,0.006901774,0.003005582,0.0007447033,0.03758926,0.002668515,0.00121833,0.02369999,0.08622736,0.5510483],"study_design_scores_gemma":[0.001275697,0.001003432,0.448746,0.0943668,0.006800157,0.002529543,0.03882102,0.0198633,0.009077889,0.05009951,0.3258516,0.001564989],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3178815,0.05278757,0.1154389,0.3883897,0.01075596,0.0105584,0.005674409,0.001489382,0.0970241],"genre_scores_gemma":[0.683602,0.01155752,0.2466169,0.04966402,0.0008249285,0.003254876,0.00188476,0.0005307487,0.002064297],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6094593,"threshold_uncertainty_score":0.7515718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7909520812482255,"score_gpt":0.6593998138296027,"score_spread":0.1315522674186228,"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."}}