{"id":"W2909981543","doi":"10.1136/annrheumdis-2018-eular.5263","title":"AB0693 Demographic, clinical, laboratory and imaging characteristics of an incidence cohort of 93 patients with large vessel gca","year":2018,"lang":"en","type":"article","venue":"Annals of the Rheumatic Diseases","topic":"Vasculitis and related conditions","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institute of Allergy and Infectious Diseases; Celgene; Medical Research Council; Canadian Institutes of Health Research; National Institutes of Health; University of California, San Francisco; European League Against Rheumatism; Medpace; Genentech; National Center for Advancing Translational Sciences; Vasculitis Foundation; AstraZeneca; Bristol-Myers Squibb","keywords":"Medicine; Cohort; Incidence (geometry); Rheumatology; Internal medicine; Retrospective cohort study; Radiology; Pediatrics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0002985533,0.0003557064,0.0004767033,0.001130181,0.001043271,0.0009786973,0.0003614627,0.0004081306,0.003691622],"category_scores_gemma":[0.001073774,0.0004998194,0.0003834089,0.001626201,0.0003240723,0.0005798396,0.0005243914,0.0006575527,0.001146552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000288467,"about_ca_system_score_gemma":0.0003133003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005920622,"about_ca_topic_score_gemma":0.003822898,"domain_scores_codex":[0.9995213,0.0000732458,0.00005486522,0.0001367787,0.00008780431,0.0001260725],"domain_scores_gemma":[0.9994,0.00008640626,0.0001873235,0.00006423581,0.00009175102,0.0001702834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000253475,0.0001198063,0.9970192,0.0000044676,0.00003226645,0.0004361254,0.0001323984,0.00002691498,0.0008372171,0.00002529369,0.0001364462,0.0009764937],"study_design_scores_gemma":[0.00001342112,0.0002308832,0.9967993,0.000003823764,0.00002661521,0.001901194,0.0004601454,0.00009936652,0.00008938336,0.00002556055,0.0003445549,0.00000570099],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989473,0.00006936133,0.00005259044,0.00001425868,0.000003380503,0.000005917259,0.000410514,0.000003157211,0.000493578],"genre_scores_gemma":[0.9986814,0.00006551622,0.00005526139,0.00002944661,0.00001139307,0.000009611255,0.0008961461,0.000004118764,0.0002470506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005920622,"threshold_uncertainty_score":0.01234967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01200166294119832,"score_gpt":0.3017141151445191,"score_spread":0.2897124522033208,"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."}}