{"id":"W4408559551","doi":"10.1016/j.ard.2025.01.050","title":"The role of multicriteria decision analysis in the development of candidate classification criteria for antisynthetase syndrome: analysis from the CLASS project","year":2025,"lang":"en","type":"article","venue":"Annals of the Rheumatic Diseases","topic":"Inflammatory Myopathies and Dermatomyositis","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Istituto di Ricovero e Cura a Carattere Scientifico; EMD Serono; National Institutes of Health; Nordic Pharma Group; Department of Health and Social Care; National Institute for Health and Care Research; Canadian Anesthesiologists' Society; National Institute of Environmental Health Sciences; Horizon Therapeutics; Manchester Biomedical Research Centre; Alexion Pharmaceuticals; AstraZeneca; Bristol-Myers Squibb; Eli Lilly and Company; American College of Rheumatology Research and Education Foundation; Pfizer; PTC Therapeutics","keywords":"Antisynthetase syndrome; Medicine; Class (philosophy); Artificial intelligence; Computer science; Immunology; Autoantibody","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":[0.063068,0.00137966,0.002394461,0.003147499,0.001190217,0.003724027,0.001766017,0.001120217,0.003218333],"category_scores_gemma":[0.1293275,0.000370438,0.004043572,0.001567382,0.0008045588,0.00176587,0.002507838,0.002417204,0.000388873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008866053,"about_ca_system_score_gemma":0.003524924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003089911,"about_ca_topic_score_gemma":0.002330131,"domain_scores_codex":[0.9550056,0.03706656,0.001983642,0.001776667,0.003256496,0.0009109089],"domain_scores_gemma":[0.7530292,0.2270647,0.006375704,0.004964746,0.006036706,0.002529025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02058748,0.00108122,0.7456369,0.0005188733,0.004940209,0.0004021494,0.0006778287,0.04446073,0.0008718139,0.004774743,0.004648563,0.1713994],"study_design_scores_gemma":[0.001410516,0.004195759,0.1662941,0.0003728596,0.003488359,0.001283648,0.0009245471,0.7985377,0.001750967,0.01792949,0.003628053,0.0001839205],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9449583,0.001698413,0.04736425,0.001510526,0.0001342641,0.000484975,0.001441606,0.0001436567,0.002263958],"genre_scores_gemma":[0.9783131,0.0001738982,0.01973672,0.0001391198,0.00006379885,0.0001739953,0.00103928,0.00007756086,0.0002825723],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.063068,"threshold_uncertainty_score":0.3335395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03047181455110507,"score_gpt":0.3537909601718494,"score_spread":0.3233191456207443,"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."}}