{"id":"W2086401822","doi":"10.3899/jrheum.120835","title":"Consensus Statements for the Use of Administrative Health Data in Rheumatic Disease Research and Surveillance","year":2012,"lang":"en","type":"article","venue":"The Journal of Rheumatology","topic":"Rheumatoid Arthritis Research and Therapies","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Clinical Research Institute; Arthritis Research Centre of Canada; University of Saskatchewan; McGill University Health Centre; Public Health Agency of Canada","funders":"Canadian Arthritis Network; Canadian Institutes of Health Research; Hospital for Sick Children; Centre Hospitalier Universitaire de Québec; University of Ottawa; Public Health Agency; Public Health Agency of Canada; University of Toronto; Dalhousie University; Université Laval","keywords":"Medicine; Observational study; Systematic review; Best practice; MEDLINE; Epidemiology; Comorbidity; Consistency (knowledge bases); Disease; Grey literature; Family medicine; Pathology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.6776532,0.003249673,0.005950068,0.0169132,0.01132178,0.01620086,0.01882729,0.02263258,0.003426831],"category_scores_gemma":[0.7719426,0.003992337,0.01225581,0.01177248,0.01500782,0.01489293,0.02674266,0.03131312,0.002502419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02809836,"about_ca_system_score_gemma":0.1274121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01066735,"about_ca_topic_score_gemma":0.007377088,"domain_scores_codex":[0.2224164,0.4908403,0.179411,0.01255354,0.0872229,0.007555771],"domain_scores_gemma":[0.1007996,0.4567167,0.05544502,0.03470947,0.336602,0.01572718],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007008055,0.0006242953,0.008065946,0.07639393,0.002739875,0.001857965,0.08496,0.008423802,0.003175993,0.1442911,0.3022976,0.3664687],"study_design_scores_gemma":[0.0008756904,0.0004964782,0.005851007,0.1778623,0.001956542,0.001652607,0.0263956,0.01267154,0.00371402,0.2247922,0.5426015,0.001130591],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.008965447,0.02807854,0.3395944,0.5529619,0.02795339,0.02009491,0.001858085,0.001088925,0.01940434],"genre_scores_gemma":[0.0888589,0.01435211,0.8219179,0.04324869,0.002822671,0.02341585,0.002424028,0.0003850255,0.002574827],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3223468,"threshold_uncertainty_score":0.3975111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3691881717495263,"score_gpt":0.4943447898731443,"score_spread":0.125156618123618,"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."}}