Pizza Makers’ Contact Dermatitis
Bibliographic record
Abstract
BACKGROUND: Contact eczema to foods, spices, and food additives can occur in occupational and nonoccupational settings in those who grow, handle, prepare, or cook food. Pizza is one of the most eaten foods in every continent, and pizza making is a common work in many countries. OBJECTIVE: We aimed to evaluate the occurrence and the causes of contact dermatitis in pizza makers in Naples. METHODS: We performed an observational study in 45 pizza makers: all the enrolled subjects had to answer a questionnaire designed to detect personal history of respiratory or cutaneous allergy, atopy; work characteristics and timing were also investigated. Every subject attended the dermatology clinic for a complete skin examination, and when needed, patients were patch tested using the Italian baseline series of haptens integrated with an arbitrary pizza makers series. RESULTS: Our results reported that 13.3% of the enrolled pizza makers (6/45) presented hand eczema, and that 8.9% (4/45) were affected by occupational allergic contact dermatitis. Diallyl disulfide and ammonium persulfate were the responsible substances. CONCLUSIONS: Performing patch tests in pizza makers and food handlers affected by hand contact dermatitis is useful. We propose a specific series of haptens for this wide working category.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".