Microbial DNA records historical delivery of anthropogenic mercury
Bibliographic record
Abstract
Mercury (Hg) is an anthropogenic pollutant that is toxic to wildlife and humans, but the response of remote ecosystems to globally distributed Hg is elusive. Here, we use DNA extracted from a dated sediment core to infer the response of microbes to historical Hg delivery. We observe a significant association between the mercuric reductase gene (merA) phylogeny and the timing of Hg deposition. Using relaxed molecular clock models, we show a significant increase in the scaled effective population size of the merA gene beginning ~200 years ago, coinciding with the Industrial Revolution and a coincident strong signal for positive selection acting on residues in the terminal region of the mercuric reductase. This rapid evolutionary response of microbes to changes in the delivery of anthropogenic Hg indicates that microbial genomes record ecosystem response to pollutant deposition in remote regions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".