Assessment of Exposure to Chlorinated Organics through the Ingestion of Moose Meat for a Canadian First Nation Community
Bibliographic record
Abstract
Moose is an important traditional food for members of the Swan River First Nation (SRFN), located in northern Alberta, Canada. As industrial development is encroaching on First Nations’ traditional territories in northern Alberta, community members are growing increasingly concerned for the sustainability and safety of their traditional foods. The Alberta Special Waste Treatment Centre (ASWTC) is an industrial incineration facility located in the core of SRFN’s traditional territory. An accidental release at the ASWTC in 1996 resulted in a significant discharge of polychlorinated biphenyls (PCBs) to the environment. In addition to this accident, the ongoing operation of the ASWTC is linked to routine low-level emissions of PCBs, polychlorinated dibenzo-p-dioxins and furans (PCDD/Fs). Since the 1996 release, levels of PCBs and PCDD/Fs have been measured in wild game tissues and the provincial government has issued consumption advisories. This study was undertaken to provide answers to the community regarding food safety and was designed to address concerns regarding PCB and PCDD/F concentrations in moose tissues. Samples of moose muscle (n=15), liver (n=13) and kidney (n=14) were collected as part of regular food harvesting activities of the SRFN in the summer and fall of 2015 and generously shared by the SRFN hunters and harvesters to allow for their inclusion into the study. A risk assessment approach was used to evaluate the potential risks to human health using hazard quotients (HQ). All HQs were below the benchmark level of 0.2 for a single pathway exposure. The results show that PCB and PCDD/F concentrations in moose tissues were low and comparable to those of meats available in Canadian supermarkets. Based on results from this study, community exposure to PCBs and PCDD/Fs from the consumption of moose tissue is low and consumption may continue at quantities documented in regional studies.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".