Allergy Alert Test for <i>p</i> -Phenylenediamine–Allergic Hair Dye Users
Bibliographic record
Abstract
BACKGROUND: Contact dermatitis to hair dyes remains a health concern. Regulations in many countries require consumer self-testing for hair dyes, but no standardized procedure exists. OBJECTIVE: The aim of this study was to develop a self-test protocol for an allergy alert test (AAT) that can elicit a self-noticeable alert signal in p-phenylenediamine (PPD)-allergic consumers. METHODS: Simulating consumer use conditions (open application for 45 minutes after mixing with a developer), PPD-positive hair dye-allergic subjects and PPD-negative control subjects were tested on the forearm and behind the ear with experimental products containing 0.05%, 0.25%, 0.75%, and 2% PPD. Reactions were self-evaluated by subjects and independently assessed by dermatologists. CONCLUSIONS: The AAT caused a reaction self-noticeable on the forearm in 90.5% (38/42) and behind the ear in 93% (39/42) of the PPD-positive subjects. This was objectified by a dermatological evaluation. The strength of the AAT response and the number of responding subjects increased with increasing PPD concentrations. Allergy alert test responses were also dependent on the reaction strength of the diagnostic patch test to PPD before the study; in subjects with (+++) patch test reactions, 19 of 19 were positive. All 48 control subjects were negative to the AAT. Therefore, the AAT protocol provides a signal indicative of an allergic reaction in PPD-allergic hair dye consumers.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".