Arsenic exposure in the Canadian general population: levels of arsenic species measured in urine, and associated demographic, lifestyle or dietary factors
Bibliographic record
Abstract
In Canada, the primary source of exposure to arsenic is food, followed by drinking water, soil, and air. Measuring inorganic arsenic in urine provides a measure of internal dose integrating all sources and routes of exposure. Urine samples were collected through the Canadian Health Measures Survey (CHMS) in 2009 to 2011 from 2538 respondents and analyzed for various inorganic related arsenic species (arsenite, arsenate, monomethylarsonic acid, dimethylarsinic acid, arsenocholine and arsenobetaine). The geometric mean of urinary dimethylarsinic acid (DMA) in the Canadian population was 3.5 (95% CI: 3.0–4.0) μg As L−1. Concentrations were significantly higher in children than in adults. Canadians who eat rice once or more per day have higher urinary concentrations. No association was found with sources of drinking water.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".