Quantifying mercury (Hg) release from coastal erosion along the Yukon coast, Canada
Bibliographic record
Abstract
Permafrost stores large amounts of mercury (Hg), locking this toxic element in frozen soils across the Arctic. Mercury and its organic form methylmercury, in particular, is a neurotoxin which accumulates along the food chain. With increasing rates of coastal erosion driven by rising air and ground temperatures, Hg is being mobilized and released into the Arctic Ocean. This process does not only threaten local ecosystems but has broader implications, as Hg might be transported over long distances or taken up by marine organisms, posing risks to both wildlife and human health. To better understand such risks, we aim to quantify the amount of Hg that is stored in permafrost and released by coastal erosion along the Yukon Coast, Canada. Samples were taken from various landscape features including permafrost cliffs, active layer, and marine sediments along the Yukon Coast and on Herschel Island-Qikiqtaruk. We analyzed over 70 samples for elemental mercury, organic carbon, nitrogen, and grain-size distribution, and supplemented these results with existing data from previous field campaigns and the literature to create a regional database. Based on these data we will first estimate Hg stocks in the upper permafrost for the Yukon Coast. Combined with coastal erosion rates we will then estimate annual Hg fluxes into the ocean for this region. Together with Hg concentrations in marine sediments our findings will provide a clearer picture of the Hg stocks, fluxes, and its fate along the Yukon Coast. These data are crucial for decision makers and might help to assess Hg exposure to Arctic wildlife and human populations, whose diet largely relies on marine biological resources.
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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 | 0.004 |
| 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".