Transboundary\nAtmospheric Pollution from Mountaintop\nCoal Mining
Bibliographic record
Abstract
Mountaintop removal coal mining impairs downstream ecosystems\nthrough\nthe delivery of nutrients, ions, and heavy-metals. Here, we show that\nthis mining also impacts ecosystems downwind, and that the suite of\nenvironmental contaminants released includes polycyclic aromatic compounds\n(PACs). We recovered a sediment core from Window Mountain Lake, located\nalong the eastern slopes of Canada’s Rocky Mountains. The sediment\ncore records a ∼30-fold increase in PAC concentrations, and\na compositional profile that matches closely with coal mined in the\nElk Valley, British Columbia, on the other side of the continental\ndivide. Selenium concentrations have also increased, paralleling a\nrise in the Elk River, which drains the coal mines. The source of\nthese contaminants is fugitive coal dust, emitted during mining and\ncarried atmospherically from Pacific to Atlantic drainage basins.\nAtmospheric PAC emissions will increase as mines expand unless mitigation\nmeasures are implemented, and our results likely apply at similar\nlarge-scale mountaintop removal coal mining operations around the\nworld.
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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 | 0.000 | 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) | 0.782 | 0.002 |
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; both teacher heads agree on what is shown here.
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".