{"id":"W4410513032","doi":"10.3899/jrheum.2025-0390.pv106","title":"GENETICS AND PROTEOMICS IN AUTOANTIBODY-DEFINED SUBGROUPS OF PATIENTS WITH SLE","year":2025,"lang":"en","type":"article","venue":"The Journal of Rheumatology","topic":"Systemic Sclerosis and Related Diseases","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Autoantibody; Proteomics; Immunology; Genetics; Bioinformatics; Antibody; Gene; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0002285906,0.0002732336,0.0003683276,0.0009448212,0.0003166014,0.0004465034,0.0001847574,0.0003928289,0.001627298],"category_scores_gemma":[0.0007899289,0.0001138767,0.000283129,0.0008784558,0.0002099984,0.0002214964,0.0002717602,0.0002627373,0.0002868235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001648836,"about_ca_system_score_gemma":0.0001013571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004577209,"about_ca_topic_score_gemma":0.0004146925,"domain_scores_codex":[0.9997157,0.00007668719,0.00004001519,0.00009067269,0.00003713007,0.00003967548],"domain_scores_gemma":[0.9996922,0.00008493812,0.0001278059,0.00002426718,0.00002454443,0.00004632218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001420578,0.00009979753,0.9685014,0.00003791034,0.000109,0.0009267707,0.0003029377,0.0001969061,0.01960014,0.00009016109,0.0002104411,0.008503873],"study_design_scores_gemma":[0.00001815767,0.0002172806,0.9961553,0.000005739659,0.00003643258,0.001775189,0.0002241768,0.0004081113,0.0007368628,0.0001602871,0.00025661,0.000005802389],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993731,0.0001894945,0.0001114137,0.00002354977,0.000002556872,0.000004331665,0.0001260914,0.000004222752,0.0001651824],"genre_scores_gemma":[0.9994327,0.00006048006,0.0001847401,0.00002468184,0.00001032287,0.000007442783,0.0001771796,0.000003321217,0.00009902429],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001627298,"threshold_uncertainty_score":0.005443871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006109551068402,"score_gpt":0.2298927904986313,"score_spread":0.2237832394302293,"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."}}