Assessment of heavy metals contamination in \ncommercial cosmetic products / Nur Farhanah Zainuddin
Bibliographic record
Abstract
Atomic Absorption Spectroscopy (AAS) technique was applied to determine and \nanalyse the concentration of heavy metal such as Zn, Pb and Ni in three different \nskin whitening creams and one herbal cream that available from retail shop in \nJengka, Pahang. The samples were digested using acid and then analyzed using \nAAS. All metals were detected in all samples but with different concentrations. \nZinc was range between 6.4 mg/kg and 17.7 mg/kg. Nickel and lead concentration \nrange were lower compared to Zn which were 3.1 mg/kg to 4.2 mg/kg and 6.2 \nmg/kg to 13.0 mg/kg respectively. The detection of Zn in the whitening creams is \nunder permissible limit as set by FAO I WHO and Health Canada 2007 standard \nwhich is 50 mg/kg. Hazard index (HI) values for HI, WI, W2 and W3 were 2.13 \nx 10-6,4.39 x 10-6 ,3.33 X 10-6 and 3.65 x 10-6 respectively. All values of HI were \nless than 1 and it is believed that there was no significant risk of non-carcinogenic \neffects. However, some of the samples contained lead exceeds the permissible \nlimit set by FAO/WHO and Health Canada which is 10 mg/kg. Overall analysis \nproved that the concentration of heavy metals in herbal cream, HI was lower \ncompared to other whitening creams, WI, W2 and W3. Since the HI values were \nlower than 1, all products were safe to use. But, it is better to take precaution in \nusing whitening creams since the presence of excess heavy metals may lead to \naccumulative toxicity in the body beyond the acceptable limit.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".