Dr. Roubille, et al reply
Bibliographic record
Abstract
To the Editor: We thank Castañeda, et al 1 for their comments on our article2. We do support comorbidity management in rheumatoid arthritis (RA), psoriatic arthritis (PsA), and psoriasis (PsO) in daily practice to ensure optimal care and outcomes, and completely agree with the recently published Spanish recommendations3. Given that patients with RA have increased risk of cardiovascular (CV) morbidity and mortality4, CV monitoring appears critical. In the CARMA (CARdiovascular in rheuMAtology) study, Castañeda, et al 5 reported that patients with RA, PsA, and PsO had higher prevalence of CV events while receiving biological therapy despite being in low disease activity for almost half of the patients. Notably, almost half of the patients also received nonsteroidal antiinflammatory drugs and/or glucocorticoids (patients with RA), which may have increased CV risk6. Regardless of the other confounding factors, these data reinforce the importance of CV monitoring and … Address correspondence to Dr. C. Roubille, University of Montreal Hospital Research Center (CRCHUM), Notre-Dame Hospital, Montreal, Quebec H2L 1S6, Canada. E-mail: camille.roubille{at}gmail.com
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.025 | 0.024 |
| 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".