Comment on: BSR/BHPR guideline for disease-modifying anti-rheumatic drug (DMARD) therapy in consultation with the British Association of Dermatologists: reply
Bibliographic record
Abstract
Sir, We would like to thank Dr Bhalla and his colleague [1] for raising an important but rather rare and unusual occurrence of a skin reaction in patients treated with MTX with previous history of radiotherapy, following the publication of DMARD Guideline [2]. The literature review reveals only one case report where MTX was involved but similar dermatological reaction was also reported with many other drugs including antibiotics, Hyocin, cytotoxics and even St John's wort. The exact mechanism of such a reaction is unknown but it is reassuring to note that the skin reaction improves soon after the discontinuation of the drugs. It would be interesting to explore if the patients reported by authors were on any other concomitant drug therapy that may have played a causal role. We appreciate the advice for inclusion of an oncologist in future but the issue relates to clinical dermatology and we were privileged to have a valued representation from British Association of Dermatologists. Disclosure statement: The author has declared no conflicts of interest.
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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 | 0.005 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.079 | 0.060 |
| Insufficient payload (model declined to judge) | 0.014 | 0.013 |
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".