Patch Testing with a Textile Dye Mix and Its Constituents in a Baseline Series
Bibliographic record
Abstract
BACKGROUND: Among the textile dyes, disperse dyes are common sensitizers. OBJECTIVE: To investigate whether patch testing with a textile dye mix consisting of eight disperse dyes would be equivalent to testing with the separate ingredients of the mix at the concentrations used in the mix. METHODS: Researchers tested 1,780 consecutive patients with a mix consisting of Disperse Blue 35, Disperse Yellow 3, Disperse Orange 1, Disperse Orange 31 (mislabeled as Disperse Orange 3), Disperse Red 1 and 17, all at 0.5%, and Disperse Blue 106 and 124, both at 0.1%, and with the ingredients at these concentrations. Testing with the labeled dyes at 1.0% was done on 500 of the patients and additionally on the remaining patients who reacted positively to the mix, any of the ingredients, p-phenylenediamine, or black rubber mix. RESULTS: Thirty-five patients (2%) reacted to the mix, and 34 patients were allergic to at least one ingredient tested at the lower concentration. CONCLUSION: The textile dye mix was as good a detector of contact allergy to the disperse dyes as was testing with any combination of the ingredients at the concentration in the mix. Increasing the concentration of the ingredients of the textile dye mix might increase the sensitivity of the mix.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".