Shining light on recent advances in microbial mercury cycling
Bibliographic record
Abstract
Mercury (Hg) is a global pollutant emitted primarily as gaseous Hg0 that is deposited in aquatic and terrestrial ecosystems following its oxidation to HgII. From that point, microbes play a key role in determining Hg’s fate in the environment by participating in sequestration, oxidation, reduction, and methylation reactions. A wide diversity of chemotrophic and phototrophic microbes occupying oxic and anoxic habitats are known to participate directly in Hg cycling. Over the last few years, new findings have come to light that have greatly improved our mechanistic understanding of microbe-mediated Hg cycling pathways in the environment. In this review, we summarize recent advances in microbially mediated Hg cycling and take the opportunity to compare the relatively well-studied chemotrophic pathways to poorly understood phototrophic pathways. We present how the use of genomic and analytical tools can be used to understand Hg transformations and the physiological context of recently discovered cometabolic Hg transformations supported in anaerobes and phototrophs. Finally, we propose a conceptual framework that emphasizes the role that phototrophs play in environmental Hg redox cycling and the importance of better characterizing such pathways in the face of the environmental changes currently underway.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".