Patch Testing with Methylchloroisothiazolinone/Methylisothiazolinone Using a New Diagnostic Mix—A Multicenter Study from the International Contact Dermatitis Research Group
Bibliographic record
Abstract
BACKGROUND: In the early 1980s, a preservative containing a mixture of methylchloroisothiazolinone (MCI) and methylisothiazolinone (MI) in a ratio of 3:1 was introduced. This mixture (mix) has been patch tested at 100 ppm (0.01%) worldwide and at 200 ppm (0.02%) in Sweden since 1986 and also in the European baseline series since 2014. OBJECTIVE: A new aqueous mix of MCI 0.015% and MI 0.2% was compared with patch testing with the 2 aqueous baseline preparations of MCI/MI 0.02% and MI 0.2%. METHODS: Four thousand three hundred ninety-seven patients with dermatitis in 12 International Contact Dermatitis Research Group dermatology departments from 3 continents were patch tested simultaneously with the 3 preparations. RESULTS: The frequency of positive patch tests to the allergens varied between 0% and 26.7% in the 12 test centers. The new mixture MCI/MI 0.215% in aqua (aq) detected significantly more patients with MCI/MI allergy than both MCI/MI 0.02% aq (P < 0.001) and MI 0.2% aq (P < 0.001) alone and combined. CONCLUSIONS: The results favor replacing the preparations MCI/MI 0.02% aq and MI 0.2% aq with the mixture MCI/MI 0.215% aq in the International Contact Dermatitis Research Group baseline series.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".