Psoriasis and Psoriatic Arthritis in the Context of the COVID-19 Pandemic: A Plenary Session From the GRAPPA 2020 Annual Meeting
Bibliographic record
Abstract
The coronavirus disease 2019 (COVID-19; caused by SARS-CoV-2) pandemic has affected the healthcare system on a global scale, and we utilized the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) 2020 annual meeting to examine how COVID-19 might affect patients with psoriatic disease (PsD) and the clinicians who care for them. Pressing issues and concerns identified included whether having psoriasis increased the risk of acquiring COVID-19, vaccine safety, and the acceptability of telehealth. The general message from rheumatologists, dermatologists, infectious disease specialists, and patient research partners was that data did not suggest that having PsD or its treatment significantly increased risk of infection or more severe disease course, and that the telehealth experience was a success overall.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.009 | 0.017 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".