{"id":"W2779862955","doi":"10.1002/acr.23503","title":"Multicenter Delphi Exercise to Identify Important Key Items for Classifying Systemic Lupus Erythematosus","year":2017,"lang":"en","type":"article","venue":"Arthritis Care & Research","topic":"Systemic Lupus Erythematosus Research","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Western Hospital; University of Toronto; University Health Network; Mount Sinai Hospital","funders":"National Institute of Arthritis and Musculoskeletal and Skin Diseases; Canadian Institutes of Health Research","keywords":"Medicine; Delphi; Rheumatology; Anti-nuclear antibody; Delphi method; Lupus nephritis; Rheumatism; Systemic lupus erythematosus; Autoantibody; Internal medicine; Artificial intelligence; Immunology; Computer science; Disease; Antibody","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1305178,0.001417137,0.0008262435,0.002954004,0.003086668,0.001969022,0.001947483,0.001274042,0.006008219],"category_scores_gemma":[0.1264386,0.0008205828,0.001667269,0.002033063,0.001991068,0.002092954,0.008082819,0.001979946,0.0009712656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003765741,"about_ca_system_score_gemma":0.009470742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001129667,"about_ca_topic_score_gemma":0.002089474,"domain_scores_codex":[0.8725654,0.1116716,0.005996098,0.002251501,0.00507898,0.002436485],"domain_scores_gemma":[0.9260066,0.05398244,0.003570332,0.003801041,0.01074701,0.001892552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.00365566,0.003048274,0.05165308,0.007898469,0.0008158891,0.001569694,0.2278543,0.01309007,0.01508028,0.02672362,0.06148775,0.5871229],"study_design_scores_gemma":[0.005509282,0.01193719,0.1810008,0.01476827,0.0009964235,0.003693625,0.3110837,0.07697986,0.01757118,0.093582,0.2817715,0.001106194],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6791977,0.001164764,0.1673555,0.01035496,0.0006879779,0.1067864,0.00150349,0.0004130311,0.03253613],"genre_scores_gemma":[0.5575905,0.0006424675,0.3351101,0.001805855,0.0001194281,0.1015658,0.0008013203,0.000050191,0.002314334],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1305178,"threshold_uncertainty_score":0.6902525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08375747076125613,"score_gpt":0.4248756839772042,"score_spread":0.341118213215948,"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."}}