Biological and photochemical production of dissolved gaseous mercury in a boreal lake. Limnology and Oceanography
Bibliographic record
Abstract
We used in situ experiments and measured depth profiles of dissolved gaseous mercury (DGM) to investigate the relative contribution of photochemical versus biological processes on the production of DGM in an oligome-sotrophic lake of the Canadian Shield. At the surface, DGM production was mainly photomediated, with reduction rates being twice as high in the wetland than in the lake. In the water column, the distribution of DGM concentrations was not strictly related to light but followed a multimodal distribution, with peaks encountered below the epilimnion at depths receiving,5 % of the incident light. Those peaks were recorded in the middle and at the bottom of the metalimnion during the ice-free season, as well as under ice cover and at the bottom of an anoxic hypolimnion. Rather than being a consequence of the bacterial mercuric reductase activity, metalimnetic DGM peaks were as-sociated with the intensity and duration of phytoplankton blooms. In situ incubation experiments also showed that DGM production ceased when samples were kept in the dark, filtered, or when an inhibitor of photosynthesis was added. Our results illustrate the important role of phytoplankton on Hg redox dynamics in the water column of lakes. Hg(0), which is emitted by natural sources or from power plant facilities and incinerators, travels over long distances
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".