Mercury (micro)biogeochemistry in polar environments
Bibliographic record
Abstract
The contamination of polar regions with mercury that is transported as inorganic mercury from lower latitudes has resulted in the accumulation of methylmercury in the food chain of polar environments, risking the health of humans and wildlife. This problem is likely to be particularly severe in coastal marine environments where active cycling occurs. Little is currently known about how mercury is methylated in polar environments. Relating observations on mercury deposition and transport through polar regions to knowledge of the microbiology of cold environments and considering the principles of mercury transformations as have been elucidated in temperate aquatic environments, we propose that in polar regions (1) variable pathways for mercury methylation may exist, (2) mercury bioavailability to microbial transformations may be enhanced, and (3) microbial niches within sea ice are sites where active microorganisms are localized in proximity to high concentrations of mercury. Thus, microbial transformations, and consequently mercury biogeochemistry, in the Arctic and Antarctic are both unique and common to these processes in lower latitudes, and understanding their dynamics is needed for the management of mercury-contaminated polar environments.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".