RETRACTED ARTICLE: Inductively coupled plasma-mass spectrometry (ICP-MS) detection of trace metal contents of children cosmetics
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
Abstract Consumption of cosmetic products in daily life in order to improve skin quality or appearance is becoming quite common. Over time, it may expose consumers to skin problems and effects caused by the absorption of chemical elements. Clean cosmetic production is important for our health. However, heavy metals can be found as impurities in raw materials or as by-products of the cosmetic production process. Women's ingestion and exposure to organic and inorganic contaminants in cosmetics through dermal absorption, due to reasons such as personal habits and characteristics of the living environment, may contribute to carcinogenic risks following daily dietary exposure. NCS ZC 81002b (Human Hair) was performed as a certified reference material in method validation. This work was conducted to evaluate element concentrations of selected elements (Al, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Hg, Cd and Pb) in 3 different brands of children's cosmetic products such as bright and colorful 22 eye shadows (7 different colour) 4 lipsticks (3 different colour) and 4 nail polishes (3 different colour) used by children in Turkey. The sample solutions were analyzed with the inductively coupled plasma mass spectrometry (ICP-MS) technique after the microwave digestion system. Consequently, the highest concentration of Al used as pigment was found in the eye shadow, lipstick and nail polish samples for the 3 brands, while the Se concentrations were the lowest in lipstick samples. The results of As, Cd, Hg, Pb, which are restricted or banned for use in cosmetic products in most countries, are below the limits set by the Food and Drug Administration (FDA) and Health Canada Product Safety Laboratory (PSL).
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.015 |
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".