Metal levels in waste pickers in Brasilia, Brazil: hair and nail as exposure matrices
Bibliographic record
Abstract
= 355) as matrices of exposure. Waste pickers were grouped according to their workplace (open waste dump: G1 and sorting plants: G2). Hair and nail samples were collected and analyzed using ICP-MS. The work duration in the facilities was significantly different between the groups with averages of 16.46 (8.48) yrs and 9.26 (6.28) yrs for hair donors in G1 and G2, and 15.92 (7.72) yrs and 8.55 (5.77) yrs for toenail donors in G1 and G2, respectively. The arithmetic means (μg/g) of cadmium, copper, lead, and manganese in hair were significantly higher in G2 (0.076 ± 0.133; 19.61 ± 18.16; 2.27 ± .56 and 3.87 ± 5.59, respectively) compared to G1 (0.069 ± 0.235; 15.72 ± 15.18; 1.72 ± 4.04 and 3.65 ± 5.5, respectively). Concentrations of arsenic, barium, cadmium, copper, cobalt, lead, manganese, and molybdenum in nail were significantly higher in G2 (0.57 ± 0.39; 22.74 ± 42.06; 0.1 ± 0.08; 22.7 ± 51.60; 0.48 ± 0.45; 4.69 ± 9.43; 19.07 ± 20.75; 1.80 ± 1.76, respectively) compared to G1 (0.40 ± 0.28; 15.32 ± 22.31; 0.08 ± 0.11; 11.91 ± 16.25; 0.37 ± 0.37; 3.94 ± 15.04; 13.01 ± 19.08; 1.16 ± 1.80, respective. Our findings suggest that the studied population was exposed to toxic metals and indicates the need for chemical exposure prevention policies to monitor chemical risk exposures in waste pickers.
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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 | 0.001 |
| 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) | 0.002 | 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".