Spatial Patterns of Mercury Accumulation in Wolverine (Gulo gulo) Across the Western Canadian Arctic: Landscape, Climate and Dietary Factors
Bibliographic record
Abstract
Mercury contamination in Arctic aquatic biota has been monitored for decades.Little information exists on mercury concentrations and drivers in terrestrial Arctic carnivores.I assessed spatial patterns of mercury concentrations in wolverine (Gulo gulo) and the relationship with environmental and dietary factors across the western Canadian Arctic.Environmental variables were measured at two scales: collection location and around a 150 km buffer.This buffer size was selected from correlation analysis between hydrogen stable isotopes in precipitation and hair from 80 individuals.Mean mercury concentrations in wolverines varied geographically in decreasing order Northwest Territories > Nunavut > Yukon.Regression models illustrated that nitrogen stable isotope ratios (diet), soil organic carbon, % cover of wet area, % of perennial snow-ice, and distance to the Arctic coast explained best this variation.Diet was the main driver of mercury concentrations in wolverines with contributions from landscape characteristics near Arctic coastal areas.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".