A cumulative human health risk assessment of the traditional diet of Indigenous youth in Western James Bay, Canada
Bibliographic record
Abstract
Environmental contaminant exposure from traditional food consumption presents a risk for Indigenous youth (i.e., children and adolescents) who live in northern Canada; however, there are few studies targeting this demographic. Essential (Co, Cr, Mn, and Se) and non-essential (As, Cd, Hg, Ni, Pb, and Sb) metals and metalloids, and fourteen polychlorinated biphenyl (PCBs) congeners in 229 tissue samples of traditionally consumed foods were analyzed (i.e., birds, fish, and large mammals) using the Arctic Monitoring and Assessment Programme protocol. Deterministic and probabilistic Monte Carlo risk assessments were used to estimate the risk of exposure to contaminants via the consumption of traditional foods; a maximum cumulative ratio calculation (MCR) to assess the risk of a varied diet of traditional foods for metals and metalloids was also carried out. There was a probabilistic risk of exposure to Hg from the consumption of pike, sucker, and walleye for children; the MCR supported the result that the risk was due mainly to Hg. Dietary exposure to PCB congener 153 (PCB-153) was primarily due to the consumption of pike and sucker. There was also a risk of exposure to three other PCB congeners (PCB-101, -180, -187) from the consumption of sucker. Our assessment indicates a risk of exposure to Hg and certain PCBs; however, the actual risk of exposure varies with season, differences in traditional food consumption, and local levels of the toxicant. Therefore, monitoring and communicating information to affected communities on an annual basis is recommended.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".