The silver linings of mercury: Reconsideration of its impacts on living organisms from a multi-timescale perspective
Bibliographic record
Abstract
Research on mercury (Hg), a naturally occurring element in Earth’s lithosphere, has been extremely hot in the past few decades due to the outbreak of a series of disastrous poisoning incidents. However, such studies might provide us a biased view towards Hg if no thorough review about its long-term effects on living organisms from a multi-timescale perspective was performed. Hg might have played a mysterious role in critical intervals (e.g., mass extinction and oceanic anoxia events) in several geologic periods due to the elevated Hg levels induced by volcanism whereas it has long been used for various purposes in human history. Therefore, it is necessary to go through previous studies and historical records of different timescales (100 to 106 yr). In this work, we conducted a thorough review of Hg knowledge at three different timescales, i.e., geologic periods (106 yr), human history (103 yr), and contemporary history (100 yr), summarizing recent advances and indicated potential research gaps. By doing so, we demonstrated that it is possible to achieve safe and sustainable Hg applications despite the current Hg crisis. However, such silver linings depend on a better understanding of ecosystem dynamics. Besides, considering the possible dire consequences of erupted Hg levels as suggested in geological periods, swift actions to mitigate the impacts of anthropogenic activities on the Hg cycle will be another key point. Overall, this review presented a unique perspective of Hg combining different timescales, shedding light on the importance of a better understanding of the global ecosystem as a whole and maintaining the sustainability of planet Earth in the future.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".