Rheumatologists and Pulmonologists at Temple University Weather the COVID-19 Storm Together
Bibliographic record
Abstract
In recent commentaries from Lancet Rheumatology and The Journal of Rheumatology 1,2, the authors eloquently illustrated the connection between the coronavirus disease 2019 (COVID-19) infection, the subsequent cytokine storm (CS) that ensues in a number of patients, and the potential efficacy of biologics that rheumatologists routinely use in their practices. Moreover, those biologics were originally investigated by rheumatologists for the treatment of numerous rheumatic conditions, including macrophage activating syndrome (MAS), a similar form of storm that resembles the one occurring in patients with COVID-193. The authors therefore conclude that rheumatologists could provide a helpful perspective in fighting the COVID-19 pandemic. The Thoracic Medicine and Surgery (TMS) Department and the Rheumatology Division at Temple University Hospital … Address correspondence to Dr. R. Caricchio, Temple University School of Medicine, 3322 N. Broad St., Philadelphia, PA 19140, USA. Email: roc{at}temple.edu.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.028 | 0.029 |
| Insufficient payload (model declined to judge) | 0.007 | 0.006 |
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".