Assessment of Lead and Iron Concentration in Cosmetics Traded in the AL-Ajilat City Market
Bibliographic record
Abstract
This study examined the concentrations of heavy metals, namely lead (Pb) and iron (Fe), in lipsticks, foundations, and face powders to ensure compliance with international safety standards and assess potential health risks. Using atomic absorption spectroscopy (AAS), samples were analyzed for heavy metal content and compared to WHO, FDA, and Health Canada guidelines. Results included that lead levels in lipsticks ranged from 0.03 to 6.15 ppm, with one sample exceeding the WHO limit of 0.01 ppm, raising safety concerns. Iron levels were alarmingly high, with a maximum of 2,566 ppm, well above the WHO guideline of 0.3 ppm. Baseline samples consistently showed low levels of lead at 0.03 ppm, but iron concentrations reached 5,735 ppm, indicating significant safety deviations. Lead concentrations in the face powders ranged from 0.03 to 2.14 ppm, with some exceeding the WHO limit, while iron levels averaged 2,613 ppm, well above acceptable limits. The study concluded that high iron levels in these cosmetic products pose health risks, stressing the need for stricter regulatory oversight and quality control in the cosmetics industry.
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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 | 0.003 | 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".