Contamination by Hazardous Elements in Low – Priced Children’s Plastic Toys Bought on the local Markets of Karachi, Pakistan
Bibliographic record
Abstract
Abstract Children’s plastics toys maybe contain toxic metals to which infants and young children can be orally exposed and may pose acute or chronic adverse health effects. The objectives of this research were to evaluate the total metal concentrations (TMCs) of Pb, Cd, Cr, Ni, Zn, Cu, and Mn in children’s plastic Toys Bought in the local markets of Karachi, Pakistan, and compared TMCs to different regulatory limits. Total 44 children’s plastic toys sourced in the Karachi local markets had analyzed by an atomic absorption spectrophotometer for heavy metals contaminations. These toy samples had divided into two groups; Plastic toys (DCT) and Plastic toys with paints or coatings (DPCT). For plastic toys, 83% (19) of samples had TMCs that exceeded European Union (EU) toy safety regulation limits for Pb, and 65% (15) of samples that exceeded for Cd. For plastic toys with paints or coating, 43% (9) of samples had TMCs that exceeded EU migration limits for Pb and 24% (5) for Cd. More than 20 samples exceeded the United States Consumer Product Safety Commission (U.S. CPSC), Canadian, and Bureau of Indian Standards (BIS) toy safety regulation limits. In toys samples (n = 44) very high TMCs of Pb (64%), Cd (45%), Cr(5%), and Ni (2%) were observed. Zn, Cu, and Mn TMCs were also existing but below the Regulation limits. The Contamination levels of Pb, Cd, Cr, and Ni and smaller extent of Zn, Cu, and Mn still pose health issues in children and may cause serious problems in their health.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".