{"id":"W3006171237","doi":"10.1002/acr2.11115","title":"A Clinically and Biologically Based Subclassification of the Idiopathic Inflammatory Myopathies Using Machine Learning","year":2020,"lang":"en","type":"article","venue":"ACR Open Rheumatology","topic":"Inflammatory Myopathies and Dermatomyositis","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; SickKids Foundation; University of Toronto","funders":"National Center for Advancing Translational Sciences; National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institutes of Health; Cure JM Foundation; Myositis Association; Genentech; Genentech Foundation for Biomedical Sciences","keywords":"Polymyositis; Autoantibody; Myositis; Juvenile dermatomyositis; Dermatomyositis; Medicine; Inclusion body myositis; Rituximab; Internal medicine; Immunology; Antibody","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007951604,0.0002025704,0.0007537067,0.00005217539,0.0002458406,0.00003988703,0.0003901728,0.0002575983,0.00005592283],"category_scores_gemma":[0.00136643,0.0001381411,0.0001201013,0.0002260663,0.0004736017,0.0001172695,0.000486662,0.000516902,0.0000136431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002029765,"about_ca_system_score_gemma":0.0002946839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007673253,"about_ca_topic_score_gemma":0.0000115508,"domain_scores_codex":[0.9977276,0.0005219083,0.0009379316,0.0003791663,0.0001765733,0.0002568421],"domain_scores_gemma":[0.9985159,0.0002309853,0.0005843972,0.0003495076,0.0001656933,0.0001535067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000964552,0.00005115602,0.9683112,0.000499612,0.00005192248,0.000057115,0.001017057,0.00004656925,0.02503236,0.00294651,0.00005022074,0.0009717577],"study_design_scores_gemma":[0.01460883,0.00392551,0.6668023,0.00240853,0.0005401293,0.003920456,0.003089172,0.2678012,0.02173703,0.0009826252,0.01284315,0.001340964],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923409,0.0006386765,0.0006057335,0.005302677,0.0001053794,0.0006703774,0.00000677268,0.00006088315,0.0002686037],"genre_scores_gemma":[0.9960572,0.0001708182,0.001715761,0.001968421,0.00001931201,0.00002311415,0.00001028918,0.00002488309,0.00001019299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3015088,"threshold_uncertainty_score":0.563323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04939989311972422,"score_gpt":0.2947462764417748,"score_spread":0.2453463833220506,"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."}}