{"id":"W2528297397","doi":"10.1002/acr.23089","title":"Rheumatology Informatics System for Effectiveness: A National Informatics‐Enabled Registry for Quality Improvement","year":2016,"lang":"en","type":"article","venue":"Arthritis Care & Research","topic":"Rheumatoid Arthritis Research and Therapies","field":"Medicine","cited_by":108,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Center for Research Resources; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Agency for Healthcare Research and Quality","keywords":"Informatics; Health informatics; Rheumatology; Quality (philosophy); Computer science; Medicine; Internal medicine; Medical physics; Engineering; Nursing","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":[],"consensus_categories":[],"category_scores_codex":[0.09425371,0.001090422,0.002324879,0.01354837,0.00210138,0.007817205,0.004555261,0.001478468,0.01505696],"category_scores_gemma":[0.1434068,0.001059336,0.001424823,0.01761082,0.001498395,0.008985743,0.009090216,0.003250078,0.008543171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007258788,"about_ca_system_score_gemma":0.04102538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005632727,"about_ca_topic_score_gemma":0.005379906,"domain_scores_codex":[0.8839146,0.04857196,0.02811612,0.01017244,0.02558312,0.003641758],"domain_scores_gemma":[0.6203201,0.08427484,0.07480545,0.07496752,0.1113809,0.03425124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001479079,0.001537854,0.1546616,0.002018167,0.0005903642,0.000205073,0.00209478,0.002544613,0.001363812,0.02333643,0.3313693,0.4787988],"study_design_scores_gemma":[0.00288512,0.002680353,0.2817728,0.003479824,0.0007947743,0.0006931265,0.001888775,0.01721091,0.005236669,0.009553737,0.6734124,0.00039157],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1103049,0.01114978,0.2605926,0.06174517,0.003072866,0.03192637,0.2793329,0.0507873,0.191088],"genre_scores_gemma":[0.2695003,0.005024248,0.4393009,0.008414257,0.003140229,0.02166469,0.2355916,0.002990857,0.01437302],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09425371,"threshold_uncertainty_score":0.4984672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03771682057788611,"score_gpt":0.3779634467814912,"score_spread":0.3402466262036051,"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."}}