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Record W2313157363 · doi:10.1021/es304969n

Contamination by Ten Harmful Elements in Toys and Children’s Jewelry Bought on the North American Market

2013· article· en· W2313157363 on OpenAlexaffabout
Mert Güney, Gérald J. Zagury

Bibliographic record

VenueEnvironmental Science & Technology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy Metal Exposure and Toxicity
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsContaminationForensic engineeringBusinessEngineeringBiology

Abstract

fetched live from OpenAlex

Toys and children's jewelry may contain metals to which children can be orally exposed. The objectives of this research were (1) to determine total concentrations (TC's) of As, Ba, Cd, Cr, Cu, Mn, Ni, Pb, Sb, and Se in toys and jewelry (n = 72) bought on the North American market and compare TC's to regulatory limits, and (2) to estimate oral metal bioavailability in selected items (n = 4) via bioaccessibility testing. For metallic toys and children's jewelry (n = 24) 20 items had TC's exceeding migratable concentration limits (European Union). Seven of seventeen jewelry items did not comply with TC limits in U.S. and Canadian regulations. Samples included articles with very high Cd (37% [w/w]), Pb (65%), and Cu (71%) concentrations. For plastic toys (n = 18), toys with paint or coating (n = 12), and brittle or pliable toys (n = 18), TC's were below the EU migration limits (except in one toy for each category). Bioaccessibility tests showed that a tested jewelry item strongly leached Pb (gastric: 698 μg, intestinal: 705 μg) and some Cd (1.38 and 1.42 μg). Especially in metallic toys and jewelry, contamination by Pb and Cd, and to a lesser extent by Cu, Ni, As, and Sb, still poses an acute problem in North America.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.003
GPT teacher head0.184
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations87
Published2013
Admission routes2
Has abstractyes

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