{"id":"W2140715962","doi":"10.3899/jrheum.100450","title":"Cardiac Magnetic Resonance Imaging in Polyarteritis Nodosa","year":2010,"lang":"en","type":"article","venue":"The Journal of Rheumatology","topic":"Vasculitis and related conditions","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Magnetic resonance imaging; Polyarteritis nodosa; Vascular disease; Nuclear magnetic resonance; Radiology; Vasculitis; Pathology; Internal medicine; Disease","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":[0.0004465873,0.0007617761,0.000531103,0.001280069,0.0006109471,0.0003770214,0.0004515617,0.001600275,0.001738393],"category_scores_gemma":[0.001586287,0.0003487573,0.0003195309,0.0005846318,0.0007841042,0.0006734953,0.0004556733,0.000947373,0.0006101886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000342494,"about_ca_system_score_gemma":0.0002393316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001856974,"about_ca_topic_score_gemma":0.001807854,"domain_scores_codex":[0.9997538,0.00004510826,0.00003923,0.00005219163,0.00003778249,0.00007191519],"domain_scores_gemma":[0.9993268,0.0002112087,0.0001551602,0.00005723991,0.00006236343,0.0001873952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"case_report","study_design_gemma":"observational","study_design_scores_codex":[0.0006174017,0.0003936287,0.3326939,0.0002047398,0.00004241416,0.6315728,0.0005716963,0.0001944092,0.02017426,0.0002145202,0.0006193903,0.01270089],"study_design_scores_gemma":[0.00009430542,0.0008755566,0.324944,0.0001089146,0.00008409363,0.6692565,0.00042834,0.0004811643,0.001751232,0.0002497545,0.001699993,0.00002623211],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9814065,0.006537663,0.0008519079,0.0006794111,0.0001035878,0.00009935981,0.0000894585,0.00006140528,0.01017085],"genre_scores_gemma":[0.995995,0.002018341,0.0005336977,0.0004656473,0.0003676828,0.00002158359,0.00007698074,0.000006613665,0.0005144874],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001856974,"threshold_uncertainty_score":0.005815506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004236175410060745,"score_gpt":0.2289495518258487,"score_spread":0.2247133764157879,"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."}}