Investigation of Cadmium Exposure in Regards to Smoking Status and Moose and Caribou Organs Consumption in Northern Canada
Bibliographic record
Abstract
Country food consumption among northern populations is associated with improved nutrition but occasionally can also increase contaminant exposure. Elevated cadmium levels in organs of moose harvested in the southern Mackenzie Mountains resulted in a food consumption notice by the Health and Social Services Department of the Northwest Territories, to recommend that people limit their consumption of liver and kidneys. Liver and kidneys of both moose and caribou are regularly consumed as country foods consumed in the Northwest Territories. The aim of this work is to report the levels and assess the determinants of cadmium exposures among communities of the Northwest Territories.The contaminants biomonitoring project includes dietary assessments (e.g. Food Frequency Questionnaire) and the collect of urine and blood samples. Participants were free to take part in any of the components of their choice (food questionnaires, hair/urine/blood sample). Cadmium was quantified using an inductively coupled plasma mass spectrometer (ICP-MS). The association between cadmium level, co-factors (age, sex) and potential sources (consumption of moose and caribou kidney and liver, smoking) were investigated.The 331 participants from the first 13 months of sample/data collection provided 144 blood and 127 urine samples. Participants who reported eating organs (liver, kidney) of moose and/or caribou did not have significantly higher cadmium levels. Instead, smoking status was significant determinant of cadmium levels in both blood (p<0.001) and urine (p=0.006). Results show cadmium levels similar to those observed in other populations in Canada.These results are supporting ongoing efforts to identify health priorities and plans in response to environmental monitoring data.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".