Human exposure to soil contaminants in subarctic Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Chemical contaminants in the Canadian subarctic present a health risk with exposures primarily occurring via the food consumption. OBJECTIVE: Characterization of soil contaminants is needed in northern Canada due to increased gardening and agricultural food security initiatives and the presence of known point sources of pollution. DESIGN: A field study was conducted in the western James Bay Region of Ontario, Canada, to examine the concentrations of polychlorinated biphenyls, dichlorodiphenyltrichloroethane and its metabolites (ΣDDT), other organochlorines, and metals/metalloids in potentially contaminated agriculture sites. METHODS: Exposure pathways were assessed by comparing the estimated daily intake to acceptable daily intake values. Ninety soil samples were collected at random (grid sampling) from 3 plots (A, B, and C) in Fort Albany (on the mainland), subarctic Ontario, Canada. The contaminated-soil samples were analysed by gas chromatography with an electron capture detector or inductively coupled plasma mass spectrometer. RESULTS: The range of ΣDDT in 90 soil samples was below the limit of detection to 4.19 mg/kg. From the 3 soil plots analysed, Plot A had the highest ΣDDT mean concentration of 1.12 mg/kg, followed by Plot B and Plot C which had 0.09 and 0.01 mg/kg, respectively. Concentrations of other organic contaminants and metals in the soil samples were below the limit of detection or found in low concentrations in all plots and did not present a human health risk. CONCLUSION: Exposure analyses showed that the human risk was below regulatory thresholds. However, the ΣDDT concentration in Plot A exceeded soil guidelines set out by the Canadian Council of Ministers of the Environment of 0.7 mg/kg, and thus the land should not be used for agricultural or recreational purposes. Both Plots B and C were below threshold limits, and this land can be used for agricultural purposes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 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".