{"id":"W4299505553","doi":"10.1136/annrheumdis-2022-eular.1133","title":"POS0162 HOW ACCURATELY CAN WE IDENTIFY RHEUMATOID ARTHRITIS BY ICD-10 CODES? A LINKAGE OF CROSS-SECTIONAL SURVEY DATA WITH CLAIMS DATA","year":2022,"lang":"en","type":"article","venue":"Annals of the Rheumatic Diseases","topic":"Rheumatoid Arthritis Research and Therapies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Medac; Bundesministerium für Bildung und Forschung; Public Health Agency of Canada; Sanofi; Pfizer; Eli Lilly and Company","keywords":"Medicine; Diagnosis code; Family medicine; Population; Health care; Cross-sectional study; Gold standard (test); Rheumatology; Rheumatism; Medical diagnosis; Rheumatoid arthritis; Internal medicine; Pathology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02837479,0.0004579312,0.0009879288,0.002906449,0.000671769,0.00247698,0.001241126,0.001131286,0.007098351],"category_scores_gemma":[0.1177522,0.0005501518,0.0008967179,0.009881147,0.000363107,0.001862822,0.002262507,0.001009963,0.002502155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003874322,"about_ca_system_score_gemma":0.001374238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008163048,"about_ca_topic_score_gemma":0.005100331,"domain_scores_codex":[0.9725687,0.01972496,0.002501232,0.00187324,0.002558329,0.0007735627],"domain_scores_gemma":[0.9174764,0.05082745,0.01474317,0.008243277,0.007618822,0.001090846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003448751,0.00009150957,0.9723102,0.0001232197,0.0006333251,0.00007180312,0.0002840099,0.0006831358,0.0001804876,0.001027094,0.005458944,0.01879145],"study_design_scores_gemma":[0.0002343675,0.0003595529,0.9586703,0.0005210656,0.0008406241,0.0004227988,0.001534979,0.01126741,0.0005182801,0.006185223,0.01938818,0.00005728358],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8670462,0.002801747,0.02747548,0.008901439,0.0007591063,0.0002961693,0.0715515,0.0002162883,0.02095213],"genre_scores_gemma":[0.9479557,0.0008827482,0.01124225,0.001508949,0.0002827467,0.0003767053,0.03504601,0.00007834118,0.00262662],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02837479,"threshold_uncertainty_score":0.150062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1369821621846936,"score_gpt":0.390719540232531,"score_spread":0.2537373780478374,"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."}}