Editorial: Environmental chemistry of mercury: sources, pathways, transformations and impact
Bibliographic record
Abstract
5. Through regional studies of mercury biogeochemical cycling, fate and transport (Graham et al., fenvc2023.1242813 (river);Fostier et al., fenvc2023.1242915 (Amazon rain forest).The papers in this Research Topic cover all aspects of Hg fate and transport and transformation in the biogeosphere with studies focused on the atmosphere, oceans, terrestrial landscapes and freshwater ecosystems, as well as examining the impacts of historical Hg contamination and the controlling factors on its fate and effects. These studies provide an insight into the important factors influencing the fate, transport and bioavailability of Hg in the environment, and demonstrate that while major advances in understanding have occurred, there is still more studies needed to further understand the factors controlling the formation and bioaccumulation of methylmercury and its impact on humans.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.014 | 0.016 |
| Insufficient payload (model declined to judge) | 0.035 | 0.032 |
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".