Formaldehyde in “Nontoxic” Nail Polish
Bibliographic record
Abstract
BACKGROUND: Nail polish is known to contain potentially hazardous chemicals that have been linked to adverse health effects after overexposure. Formaldehyde is used as an antimicrobial, preservative, and nail hardener in select nail products, yet it is a recognized carcinogen and potent allergen in allergic contact dermatitis. OBJECTIVE: The aim of this study was to investigate whether formaldehyde is present in nail polishes marketed as formaldehyde-free. METHODS: Twenty-nine cosmetic nail polishes were purchased for analysis; of these, 28 were advertised as formaldehyde-free and/or did not declare formaldehyde in their ingredient lists. Initial testing was pursued using the chromotropic acid method, which uses a red-purple color change to indicate the presence of formaldehyde. Products were subsequently analyzed at least twice using high-performance liquid chromatography, quantifying formaldehyde amount above the detection limit of 2 ppm. CONCLUSIONS: High-performance liquid chromatography analysis found 5 of 29 products containing formaldehyde, 4 of which were advertised as formaldehyde-free. All other products were negative for formaldehyde (<2 ppm). Further investigation is warranted among brands testing positive and whether multiple products within the same line contain formaldehyde. Nail products must be labeled appropriately to avoid adverse reactions among individuals with cutaneous sensitivities.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 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".