Correlation between pH and irritant effect of cleansers marketed for dry skin
Bibliographic record
Abstract
BACKGROUND: Although it is important that dermatologists and the general population know the irritation potential of products marketed for dry skin used for body cleansing, this information is not usually available. OBJECTIVE: To assess the irritative effect of different soaps and liquid cleansers recommended for sensitive skin. To study the correlation of the irritation effect of each substance with its pH and with the presence or absence of syndet in the product. METHODS: Seventeen products marketed for dry skin and 12 common soaps used by the general population were studied. Fresh soap emulsions (8%) were applied to the volar side of the right forearm of 30 individuals with sensitive skin for 5 consecutive days using aluminum chambers. The appearance of irritation (erythema, scaling and fissures) was recorded, scored, and expressed in an Irritation index (IrIn). The pH of each solution was measured. RESULTS: Products with a low IrIn were White Dove (Dove, Lever Pond's, Toronto, Ontario, Canada), Dove Baby, Cetaphil (bar) (Cetaphil, Gulderma Lab., Forth Worth, TX, USA), Dove liquid cleanser for hands, Dove pink, and Aderma (Adenma, Pierre Fabre, Dermo-Cosmetique, Boulagne, France). Most corresponded to syndet products. Among the most used brand-name soap, Camay Classic (Camay, Procter & Gamble de Mexico, México, U.F.) had the lowest IrIn. Dove Baby was the only product with a neutral pH. A significant correlation between pH and the IrIn of cleansers was found (P < 0.006). CONCLUSIONS: Most products recommended for sensitive skin have a considerable irritation effect, which is related to the pH of the product. Better regulation of advertisement specifications including the pH level and type of cleanser contained is necessary for the majority of soaps and cleansers.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".