Mercury Methylation in the Epilithon of Boreal Shield Aquatic Ecosystems
Bibliographic record
Abstract
Methylation rates by periphyton growing on the rocky shore of a remote boreal shield lake were measured over diurnal cycles at temperatures representative of summer and fall conditions. The measurements were carried out in vitro with natural communities grown on artificial Teflon substrates submerged along the lake's shore for 1-2 years. At temperatures above 20 degrees C, epilithon Hg methylation rates were fast and reached a steady state within 12 h upon exposure to 2 ng L(-1) of inorganic mercury. A variety of inhibitors were used to identify which microorganisms in the epilithic biofilm are responsible for the methylation. The addition of molybdate, which is believed to suppress the activity of sulfate-reducing bacteria, decreased methylmercury production rates by 60% in both light and dark experiments. The prokaryote inhibitor chloramphenicol reduced the methylation rate by 40% only during dark periods whereas an algal inhibitor (DCMU), which suppresses photosynthesis, decreased the methylation rate by 60% during light periods. Results of this study reveal that epilithon communities may be a significant source of MeHg to higher aquatic organisms in lakes and that the integrity of the epilithic biofilm is important for its ability to methylate 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 | 0.000 | 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".