Mercury methylation in the hypolimnetic waters of lakes with and without connection to wetlands in northern Wisconsin
Bibliographic record
Abstract
Rates of Hg methylation and demethylation were measured in anoxic hypolimnetic waters of two pristine Wisconsin lakes using stable isotopes of Hg as tracers. One of the lakes is a clear-water seepage lake situated in sandy terrain with minimal wetland influence. The other is a dark-water lake receiving channelized inputs from a relatively large terrestrial wetland. Methyl mercury (MeHg) accumulated in the anoxic hypolimnia of both lakes during summer stratification, reaching concentrations of 0.8 ng·L1in the clear-water lake and 5 ng·L1in the dark-water lake. The stable isotopic assays indicated that rate constants of Hg(II)methylation (Km) ranged from 0.01 to 0.04·day1in the clear-water lake and from 0.01 to 0.09·day1in the dark-water lake, depending on the depth stratum. On average, Kmwas threefold greater in the dark-water lake. Hypolimnetic demethylation rate constants (Kdm) averaged 0.03·day1in the clear-water lake and 0.05·day1in the dark-water lake. These methylation rates were sufficient to account for the observed accumulation of MeHg in hypolimnetic water during summer in both lakes. Despite substantial export of MeHg from the wetland to the dark-water lake, our study indicates that in-lake production and decomposition of MeHg dominated the MeHg cycle in both lakes.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".