Allergen Content of Best-Selling Ethnic Versus Nonethnic Shampoos, Conditioners, and Styling Products
Bibliographic record
Abstract
BACKGROUND: Hair products are a potential cause of allergic contact dermatitis. There are limited data on the allergen content of ethnic hair products. OBJECTIVE: To identify allergens unique to ethnic hair products (shampoos, conditioners, styling products) and provide a resource for low allergen hair care products for patients with ethnic hair types. METHODS: The top 100 best-selling shampoos, conditioners, and styling products for ethnic and nonethnic hair products were determined from 3 major online retailers (Walmart, Target, Walgreens). Allergen was defined as presence on the 2017 American Contact Dermatitis Society Core 80 allergen list. RESULTS: The 2017 American Contact Dermatitis Society Core 80 allergens were tabulated for ethnic and nonethnic shampoos, conditioners, and styling products. A list of low-allergen shampoos, conditioners, and styling products was identified. Fragrance was the most common allergen for ethnic shampoos, conditioners, and styling products. Other notable allergens included methylchloroisothiazolinone/methylisothiazolinone, formaldehyde releasers, cetyl steryl alcohol, tocopherol, decyl glucoside, sodium benzoate, and phenoxyethanol. CONCLUSIONS: This study identifies important differences in allergens found in products marketed for ethnic hair compared with those marketed for nonethnic hair.
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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".