The High Complexity of Plastic Additives in Hand Wipes
Bibliographic record
Abstract
Extensive and long-term applications have resulted in global distributions of plastic additives (PAs). To facilitate the understanding of human exposure to PAs, the present study investigated the abundances and profiles of a broad range of PAs on human hands via hand wipe sampling. Sixty out of 160 PAs were detected in >50% of hand wipes collected from 30 children and 45 adults, among which a number of organophosphate esters (OPEs) and synthetic antioxidants that have rarely or never been investigated in prior studies. The total masses of PAs ranged from 650 to 87 030 ng (median: 6110 ng) and 1230 to 19360 ng (median: 5600 ng) in adults’ and children’s hand wipes, respectively. By categories, phthalates (PAEs) represented the most abundant group of PAs, followed by non-PAE plasticizers, UV stabilizers, OPEs, antioxidants, and bisphenol analogues. Children exhibited greater PA levels per square centimeter of hand surface, indicating elevated exposure compared with adults. Strong correlations existed for many PAs between adults and children or within each subpopulation, indicating close connections between the two subpopulations in the exposure profiles. The great complexity of plastic additives on hands raises the need for future investigations on human exposure pathways and potential health risks from the “cocktail” effects.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".