{"id":"W4397001445","doi":"10.1016/j.semarthrit.2024.152468","title":"Personalizing cardiovascular risk prediction for patients with systemic lupus erythematosus","year":2024,"lang":"en","type":"article","venue":"Seminars in Arthritis and Rheumatism","topic":"Systemic Lupus Erythematosus Research","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Heart, Lung, and Blood Institute; Canadian Institutes of Health Research; Ipsen; Horizon Therapeutics; Massachusetts General Hospital; Novo Nordisk; Celltrion; National Cancer Institute; Kiniksa Pharmaceuticals; AstraZeneca; Eli Lilly and Company; Bristol-Myers Squibb; Gilead Sciences; National Institutes of Health; Lupus Foundation of America","keywords":"Medicine; Internal medicine; Lupus erythematosus; Systemic lupus; Dermatology; Systemic disease; Systemic lupus erythematosus; Cardiology; Immunology; Immunopathology; Disease; 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":[0.002723614,0.0004021648,0.0003935981,0.0005818143,0.0002001184,0.0005315461,0.0002334686,0.0003147262,0.001033577],"category_scores_gemma":[0.01068774,0.000120602,0.0003502125,0.0004755351,0.0001366085,0.0004327435,0.0005490831,0.0006417118,0.0002520389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000153587,"about_ca_system_score_gemma":0.0003020274,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007935722,"about_ca_topic_score_gemma":0.001325162,"domain_scores_codex":[0.9988514,0.0006977656,0.00009570178,0.0001292597,0.0001635787,0.00006221047],"domain_scores_gemma":[0.9973421,0.00166444,0.0004986738,0.0002123513,0.0001716077,0.0001109659],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003244033,0.0001021794,0.9342096,0.00004492443,0.0001334023,0.00006040977,0.0001301605,0.003039448,0.0003591766,0.00007692149,0.0008920424,0.06062734],"study_design_scores_gemma":[0.0002013016,0.001043817,0.9331108,0.0001420154,0.0003166148,0.0008325191,0.0003097805,0.05819084,0.001287198,0.001751802,0.002779076,0.00003416213],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880716,0.001026737,0.007264404,0.0009116309,0.00003401487,0.00007012932,0.0005245159,0.0001138448,0.001983141],"genre_scores_gemma":[0.9958283,0.0002311326,0.003370897,0.00009358268,0.00004887203,0.000028159,0.0002523664,0.000003445232,0.0001431267],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002723614,"threshold_uncertainty_score":0.01440406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008138315025922509,"score_gpt":0.2342125675896516,"score_spread":0.2260742525637291,"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."}}