Determination of Cadmium, Lead, Nickel and Zinc in Hair Cream Products on the Nigerian Market
Bibliographic record
Abstract
In this study, heavy metals like Pb, Cd, Ni and Zn were quantitatively estimated using AAS. The results indicate that among the toxic heavy metals, Pb, Ni and Pb were exceeding the Health Canada permissible limit fixed for hair creams in most of the hair cream samples, but Cadmium was found appreciably well below the permissible limit. At 95% confidence level, p < 0.05, there is a significant difference in the values of the concentration of heavy metals among the hair cream samples used in this study, except for Cadmium concentrations which at this confidence level, p > 0.05, has no significant difference. In conclusion, enforcement of strict and separate regulatory guidelines and promotion of Good Analytical Practice (GAP) and Good Manufacturing Practices (GMP) is suggested for hair cream cosmetics by Health Canada and other regulatory agencies in Nigeria. This study presents the status of heavy metals in marketed hair cream cosmetic formulations and also provides a simple and convenient AAS method which can effectively be adopted at Industrial level for the quality control and standardization of hair care cosmetic preparations and other related products. Keywords: Hair cream cosmetic, Heavy metals, AAS, GAP, GMP
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".