{"id":"W4205864345","doi":"10.1136/annrheumdis-2021-eular.1632","title":"OP0006 ASSOCIATIONS OF BASELINE USE OF BIOLOGIC OR TARGETED SYNTHETIC DMARDS WITH COVID-19 SEVERITY IN RHEUMATOID ARTHRITIS: RESULTS FROM THE COVID-19 GLOBAL RHEUMATOLOGY ALLIANCE","year":2021,"lang":"en","type":"article","venue":"Annals of the Rheumatic Diseases","topic":"COVID-19 Clinical Research Studies","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University; Impact; Research Canada","funders":"National Institutes of Health; National Institute for Health and Care Research; Medpace; Gilead Sciences; Sanofi; Bristol-Myers Squibb; Amgen","keywords":"Medicine; Rheumatoid arthritis; Tocilizumab; Internal medicine; Abatacept; Rheumatology; Hydroxychloroquine; Logistic regression; Concomitant; Tofacitinib; TNF inhibitor; Adalimumab; Janus kinase inhibitor; Golimumab; Rituximab; Coronavirus disease 2019 (COVID-19); Disease","routes":{"ca_aff":true,"ca_fund":false,"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":[0.003377917,0.0006871052,0.0008585357,0.001013531,0.0003433938,0.001180345,0.0006193467,0.0008781772,0.003326261],"category_scores_gemma":[0.007523645,0.0003379137,0.001866648,0.002226918,0.0003574956,0.0008822317,0.001106055,0.001145403,0.0003961459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002376192,"about_ca_system_score_gemma":0.00047014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003451328,"about_ca_topic_score_gemma":0.004034163,"domain_scores_codex":[0.9970257,0.00123161,0.0004706149,0.0004289,0.000511935,0.0003312062],"domain_scores_gemma":[0.9925184,0.002219664,0.003604161,0.0004722615,0.0005958012,0.0005895792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004698721,0.0001198532,0.9842623,0.0003417518,0.003501054,0.00004113892,0.00004792937,0.0001143699,0.0004301073,0.00007386864,0.00114849,0.005220457],"study_design_scores_gemma":[0.0003780569,0.000471947,0.9963682,0.00005401934,0.001215664,0.00008602968,0.00008600761,0.000088234,0.00008886838,0.00005824014,0.001095114,0.000009664919],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9662594,0.009168627,0.000463264,0.0005490672,0.0001271845,0.00008802053,0.01920851,0.00002537441,0.004110522],"genre_scores_gemma":[0.9901159,0.001442535,0.0003372185,0.0002272161,0.0001614407,0.00007295233,0.00676451,0.00001049432,0.0008676372],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003451328,"threshold_uncertainty_score":0.01786435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1498753205652555,"score_gpt":0.4255400967280882,"score_spread":0.2756647761628327,"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."}}