{"id":"W2796817696","doi":"10.3899/jrheum.170770","title":"Absence of Fibrosis and Inflammation by Cardiac Magnetic Resonance Imaging in Rheumatoid Arthritis Patients with Low to Moderate Disease Activity","year":2018,"lang":"en","type":"article","venue":"The Journal of Rheumatology","topic":"Rheumatoid Arthritis Research and Therapies","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Heart, Lung, and Blood Institute; U.S. Department of Veterans Affairs","keywords":"Medicine; Internal medicine; Cardiology; Rheumatoid arthritis; Interquartile range; Cardiac magnetic resonance imaging; Ejection fraction; Heart failure; Fibrosis; Magnetic resonance imaging; Body surface area; Cardiac function curve; Radiology","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":[0.0007383905,0.0004106846,0.0004789561,0.001027767,0.0005997539,0.0005224138,0.0002510209,0.0005617938,0.001579198],"category_scores_gemma":[0.003187002,0.0002556245,0.0002299277,0.0004184509,0.0005405219,0.0003742565,0.0003967403,0.0003728155,0.0003622831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000174437,"about_ca_system_score_gemma":0.0001724722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001051166,"about_ca_topic_score_gemma":0.001403948,"domain_scores_codex":[0.9994042,0.000188858,0.00009436168,0.0001299524,0.0001175568,0.00006509382],"domain_scores_gemma":[0.9982218,0.0003906863,0.0008496126,0.00007447159,0.0001424991,0.000320932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004628263,0.00006549396,0.9970586,0.00001598551,0.00003441085,0.0002509884,0.0000745399,0.00002098108,0.0009642267,0.000008882609,0.00003816449,0.001004887],"study_design_scores_gemma":[0.00004059431,0.0004519784,0.9970316,0.000008256852,0.00003401091,0.001993819,0.0001090271,0.0001184721,0.0001022017,0.00001971624,0.00008654218,0.000003780471],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999195,0.0003428294,0.0000585502,0.00003445956,0.000005061961,0.000007634948,0.0000348133,0.000002632091,0.0003189596],"genre_scores_gemma":[0.9997754,0.00004075147,0.00005224126,0.00001743827,0.00001354784,0.000003557029,0.00004593028,6.270583e-7,0.00005054688],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001579198,"threshold_uncertainty_score":0.005282938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003778381288947386,"score_gpt":0.2221442853433905,"score_spread":0.2183659040544431,"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."}}