Physical and Biological Factors Affecting Mercury and Perfluorinated Contaminants in Arctic Char (<i>Salvelinus alpinus</i>) of Pingualuit Crater Lake (Nunavik, Canada) + Supplementary Appendices (See Article Tools)
Bibliographic record
Abstract
Pingualuk Lake fills a deep crater in the Parc National des Pingualuit on the Ungava Peninsula (Nunavik, Canada) and is isolated from nearby surface waters. The main objectives of this study were to determine and compare the concentrations of two atmospherically derived contaminants, mercury and perfluorinated chemicals (PFCs), in the lake water column and fish of Pingualuk Lake and to assess the physical and biological factors influencing contaminant concentrations. Mercury concentrations in arctic char muscle tissue were comparable to those of char in other Arctic lakes, while the total amount of PFCs was below reported levels for remote lakes in the Arctic and elsewhere. Stable isotope and stomach content analyses were made to investigate the feeding ecology of the Pingualuk Lake arctic char population and indicated the possibility of multiple feeding groups. Genetics characteristics (MH and mtDNA) of fish from Pingualuk Lake revealed that this population is likely distinct from that of nearby Laflamme Lake. However, both arctic char populations exhibit differential variation of their allele families. Physical characteristics determined for Lake Pingualuk revealed that the water column was inversely stratified beneath the ice and extremely transparent to visible and ultraviolet radiation. The highest mercury concentrations (3 – 6 pg mL-1 TH g) occurred just beneath the ice surface in each lake. Pingualuk Lake, given its near pristine state and exceptional limnological features, may serve as a most valuable reference ecosystem for monitoring environmental stressors, such as contaminants, in the Arctic.
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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) | 0.001 | 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".