Recent advances in the study of mercury methylation in aquatic systems
Bibliographic record
Abstract
With increasing input of neurotoxic mercury to environments as a result of anthropogenic activity, it has become imperative to examine how mercury may enter biotic systems through its methylation to bioavailable forms in aquatic environments. Recent development of stable isotope-based methods in methylation studies has enabled a better understanding of the factors controlling methylation in aquatic systems. In addition, the identification and tracking of the hgcAB gene cluster, which is necessary for methylation, has broadened the range of known methylators and methylation-conducive environments. Study of abiotic factors in methylation with new molecular methods (the use of stable isotopes and genomic methods) has helped elucidate the confounding influences of many environmental factors, as these methods enable the examination of their direct effects instead of merely correlative observations. Such developments will be helpful in the finer characterization of mercury biogeochemical cycles, which will enable better predictions of the potential effects of climate change on mercury methylation in aquatic systems and, by extension, the threat this may pose to biota.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".