Patch Testing with a New Composition of the Mercapto Mix—A Multicenter Study from the International Contact Dermatitis Research Group
Bibliographic record
Abstract
BACKGROUND: Mercaptobenzothiazole compounds are associated with allergic contact dermatitis caused by rubber products. Several screening substances have been used for patch testing. OBJECTIVE: To compare the frequency of positive test reactions to a mercapto mix containing a higher concentration of 2-mercaptobenzothiazole with reactions to the combination of 2-mercaptobenzothiazole 2.0% and mercapto mix 2.0%. METHODS: There were 7103 dermatitis patients in 12 International Contact Dermatitis Research Group dermatology departments who were patch tested with 2-mercaptobenzothiazole 2.0% petrolatum (pet.), mercapto mix 2.0% pet., and mercapto mix 3.5% pet. RESULTS: Contact allergy to the 3 test preparations varied among the 12 centers: 2-mercaptobenzothiazole 2.0% pet. (0-2.4%), mercapto mix 2.0% pet. (0-4.9%), and mercapto mix 3.5% pet. (0-1.4%). 2-Mercaptobenzothiazole 2.0% and mercapto mix 2.0% detected a few more positive patients compared with mercapto mix 3.5%, but the difference was statistically insignificant (mercapto mix 2.0% pet., P = 1.0; 2-mercapto-benzothiazole 2.0% pet., P = 0.66). CONCLUSIONS: Mercapto mix 3.5% pet. is not better than 2-mercaptobenzothiazole 2.0% and mercapto mix 2.0% by a difference that is significant. By using only 1 test preparation (mercapto mix 3.5%), an additional hapten could be tested. No cases of suspected/proven patch test sensitization were registered.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".