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 \nthe Porcupine Watershed, east of Timmins, Ontario, as an area of concern due to a variety of \npotential point-source contaminants from over a century of forestry, mining, and \nurbanization. Further study of the watershed was necessary to determine the existence and, if \npresent, the extent of contamination. This study evaluated metal uptake and its relationship with \nbody condition of Castor canadensis, Ondatra zibethica, Lontra canadensis, and Mustela vison. \nResults indicated that in the industrial area, Castor canadensis had an increase of 5% in body \ncondition and 26% decrease in body condition in Ondatra zibethica. Moving up the trophic level, \naquatic carnivores, Lontra canadensis had a 46% lower body condition in industrial areas, while \nMustela vison’s body condition was lower in the industrial area by 33%. In both trophic levels, \narsenic, cadmium, cobalt, copper, iron, and manganese levels in tissues were significantly higher \n(P<0.05) in the industrial area compared to the reference areas. These results indicate that \nbioavailability of certain metals is higher in the industrialized area of the Porcupine Watershed \nand that potentially, some pressures on fauna health may exist. No evidence of site-influence or \nenhanced levels were observed for mercury, lead, antimony, selenium, chromium or zinc. No \ndirect link between higher point-source bioavailability of metals and current and past industry, \nurban development nor natural variability in local geology was found. However, if remedial \nmeasures are implemented, all parties should be involved. In order to protect and restore the \nhealth of the watershed, further investigation is necessary to determine the point- sources of the \nidentified metals.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".