{"id":"W4401665200","doi":"10.1136/ard-2024-225868","title":"Plasma proteome profiling in giant cell arteritis","year":2024,"lang":"en","type":"article","venue":"Annals of the Rheumatic Diseases","topic":"Vasculitis and related conditions","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Sinai Hospital; McMaster University; St. Joseph’s Healthcare Hamilton","funders":"National Center for Advancing Translational Sciences; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Center for Individualized Medicine, Mayo Clinic; National Institute of Allergy and Infectious Diseases; National Heart, Lung, and Blood Institute; National Center for Research Resources","keywords":"Giant cell arteritis; Proteome; Medicine; Plasma cell; Disease; Blood proteins; Arteritis; Computational biology; Bioinformatics; Immunology; Pathology; Internal medicine; Vasculitis; Biology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004792516,0.0003260402,0.0002868278,0.0008838847,0.0001772577,0.0004548296,0.0001470684,0.0003753382,0.0003680417],"category_scores_gemma":[0.0008421667,0.000106557,0.000225523,0.0006032792,0.0001621365,0.00020138,0.0002458418,0.0002541581,0.0001232455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000144717,"about_ca_system_score_gemma":0.0001193172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000432204,"about_ca_topic_score_gemma":0.0004101041,"domain_scores_codex":[0.9997562,0.00006243963,0.00002376522,0.00007925452,0.00005742922,0.00002095173],"domain_scores_gemma":[0.9996778,0.00007928406,0.0001505457,0.00001793349,0.00004569687,0.00002880582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001764522,0.000156863,0.4982277,0.0003387911,0.0003473676,0.001118486,0.0002872669,0.001431292,0.4554291,0.00009772188,0.0004490299,0.04035183],"study_design_scores_gemma":[0.00003490978,0.0005474724,0.9492377,0.00004460755,0.0001471897,0.003587835,0.0001922948,0.004784893,0.03991487,0.0003428156,0.001146215,0.00001935164],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967129,0.001412155,0.001284135,0.00005422088,0.000008049667,0.00001228741,0.000326085,0.00003062367,0.0001594457],"genre_scores_gemma":[0.9970351,0.0003884678,0.002015969,0.00005514611,0.00001513511,0.0000133441,0.0003582628,0.000003946905,0.0001145304],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008838847,"threshold_uncertainty_score":0.002534568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02356396143262147,"score_gpt":0.2857400179875791,"score_spread":0.2621760565549577,"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."}}