Metal and body condition assessment in aquatic furbearers from the Porcupine River system, Timmins, Ontario
Bibliographic record
Abstract
In 2014, MOECC, MNRF, local First Nations, the City of Timmins, and local mines designated the Porcupine Watershed, east of Timmins, Ontario, as an area of concern due to a variety of potential point-source contaminants from over a century of forestry, mining, and urbanization. Further study of the watershed was necessary to determine the existence and, if present, the extent of contamination. This study evaluated metal uptake and its relationship with body condition of Castor canadensis, Ondatra zibethica, Lontra canadensis, and Mustela vison. Results indicated that in the industrial area, Castor canadensis had an increase of 5% in body condition and 26% decrease in body condition in Ondatra zibethica. Moving up the trophic level, aquatic carnivores, Lontra canadensis had a 46% lower body condition in industrial areas, while Mustela vison’s body condition was lower in the industrial area by 33%. In both trophic levels, arsenic, cadmium, cobalt, copper, iron, and manganese levels in tissues were significantly higher (P<0.05) in the industrial area compared to the reference areas. These results indicate that bioavailability of certain metals is higher in the industrialized area of the Porcupine Watershed and that potentially, some pressures on fauna health may exist. No evidence of site-influence or enhanced levels were observed for mercury, lead, antimony, selenium, chromium or zinc. No direct link between higher point-source bioavailability of metals and current and past industry, urban development nor natural variability in local geology was found. However, if remedial measures are implemented, all parties should be involved. In order to protect and restore the health of the watershed, further investigation is necessary to determine the point- sources of the identified metals.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".