Methylmercury production in high arctic wetlands
Bibliographic record
Abstract
Mercury is present at elevated levels in the top predators living in High Arctic ecosystems. Because only methylmercury (MeHg) bioaccumulates in food chains, the sources need to be identified. In temperate environments, wetlands are considered to be the principal sources of MeHg, with sulfate-reducing bacteria (SRB) thought to be responsible. The present study investigated whether High Arctic wetlands produced MeHg and whether SRB were involved in MeHg formation. Frozen soil was collected from 18 High Arctic wetlands before ground thaw, and when analyzed for MeHg, values were low, averaging 0.065 ng/g. When soils were incubated for 30 and 60 d at typical summer Arctic soil temperatures (4 degrees C and 8 degrees C), MeHg increased up to 100-fold. These laboratory observations were consistent with field measurements of wetland surface water, where MeHg concentrations increased from near detection limits (0.02 ng/L) at the inflow to an average of 1.21 ng/L at the outflow. Both laboratory and field data showed MeHg production in High Arctic wetlands. The prevalence of SRB in soil was low, however, and DNA analysis of the dissimilatory sulfate-reductase gene specific to SRB was positive at only one site. The present study showed that wetlands in the High Arctic can produce MeHg but that SRB may not the dominant mercury methylators.
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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".