Coupling of methyl and total mercury in a minerotrophic peat bog in southeastern Sweden
Bibliographic record
Abstract
During most of an annual cycle, we studied the temporal variation of total mercury (HgT) and methyl mercury (MeHg) in unfiltered and filtered (0.45 µ) peat water from a minerotrophic peat bog in southeastern Sweden. MeHg in bulk water ([MeHgT]) and total Hg in filtered water in discharge water from the peat bog ([HgD]) were an order of magnitude higher than in upland runoff water entering the peat bog. At the discharge end, peat-water [HgD] and [MeHgD] ranged from 8 to 54 pmol·L1 and from 1 to 32 pmol·L1, respectively. Whereas the variation of [MeHgT] was explained by changes in [MeHgD], the variation of inorganic HgT [IHgT] = [HgT] [MeHgT] was explained by changes in particle-bound IHg [IHgP] = [IHgT] [IHgD]. Filterable organic matter and sulfide in the water both correlated poorly with [HgD]. Neither did the amount of HgT in precipitation and upland runoff water correlate well with the estimated discharge of HgD from the peat bog. However, there was a strong correlation between [HgD] and [MeHgT] in the peat water (r = 0.96). Furthermore, a significant fraction of HgD was MeHg (mean 28%; range 860%). These results suggest that methylation increased the mobility of Hg.
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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 | 0.000 |
| 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) | 0.000 | 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".