{"id":"W3083753684","doi":"10.1136/rmdopen-2020-001357","title":"Recognising the spectrum of scleromyositis: HEp-2 ANA patterns allow identification of a novel clinical subset with anti-SMN autoantibodies","year":2020,"lang":"en","type":"article","venue":"RMD Open","topic":"Inflammatory Myopathies and Dermatomyositis","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Computer Research Institute of Montréal; Cégep de l'Abitibi Témiscamingue; Jewish General Hospital; Hôpital du Sacré-Cœur de Montréal; Université de Montréal; University of Calgary; McGill University; Centre Hospitalier de l’Université de Montréal","funders":"Canadian Institutes of Health Research; Scleroderma Association of British Columbia","keywords":"Medicine; IIf; Autoantibody; Interstitial lung disease; Anti-nuclear antibody; Myositis; Rheumatology; Scleroderma (fungus); Pathology; Myopathy; Overlap syndrome; Internal medicine; Disease; Lung; Immunology; 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":[0.0001866026,0.0004826169,0.0002249749,0.000530209,0.0002533032,0.0002698512,0.0001788647,0.0003287409,0.001946494],"category_scores_gemma":[0.0006914081,0.0001587185,0.0001782609,0.0002491019,0.000315424,0.0002622636,0.0003088786,0.000161993,0.0004016766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009938218,"about_ca_system_score_gemma":0.0001239367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002527719,"about_ca_topic_score_gemma":0.0003443484,"domain_scores_codex":[0.9998267,0.00003091439,0.00002658951,0.00005151542,0.00002385323,0.00004042489],"domain_scores_gemma":[0.999706,0.00006786841,0.0001101817,0.00002029382,0.00003153532,0.00006407312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003422677,0.00005786292,0.9650506,0.00004134598,0.00002936265,0.01270031,0.0001545532,0.00008251807,0.01616018,0.00004710193,0.0001350176,0.005198853],"study_design_scores_gemma":[0.00003511495,0.0006780386,0.8800444,0.00002261236,0.00004874939,0.1153253,0.0002983144,0.0005226164,0.002325006,0.00006511698,0.0006274484,0.000007160262],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992316,0.0002053283,0.0001682005,0.00001301397,0.000001886149,0.000005518388,0.00003161612,0.000004685704,0.0003381604],"genre_scores_gemma":[0.9996463,0.00005652996,0.000135921,0.00001131555,0.00001129078,0.00000409554,0.0000659746,0.000001212809,0.00006728071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001946494,"threshold_uncertainty_score":0.006511629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07752857529124575,"score_gpt":0.339296525072569,"score_spread":0.2617679497813232,"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."}}