Mercury Levels and Mercury Methylation and Demethylation Rate Potentials in Canadian High Arctic Sea Ice
Bibliographic record
Abstract
Climate warming and the shift from multi-year to first-year sea ice have significant, yet uncertain impacts on mercury cycling in the Arctic. EPA Method 1631 was successfully adapted for clean, ultra-trace total mercury analysis in sea ice. Dimethyl mercury was not detected, and methyl mercury quantification using the ascorbic acid method proved to be effective. Results showed that total mercury and methyl mercury concentrations were higher in multi-year ice than in first-year ice. In-situ methylation and demethylation were inconsistent and marginally detectable in sea ice. There was no correlation between methyl mercury concentrations and average methylation and demethylation potentials in sea ice. The findings from this thesis suggest that in-situ mercury methylation in sea ice is not the dominant source of methyl mercury to coastal Arctic environments, as previously hypothesized. Instead, longer-term storage of methyl mercury, likely sourced from oceanic water and particles, are inferred as more probable sources.
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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 | 0.002 | 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".