Biological Mercury Hotspots in the Northeastern United States and Southeastern Canada
Bibliographic record
Abstract
Biological mercury (Hg) hotspots were identified in the northeastern United States and southeastern Canada using a data set of biotic Hg concentrations. Eight layers representing three major taxa and more than 7300 observations were used to locate five biological Hg hotspots and nine areas of concern. The yellow perch and common loon were chosen as indicator species for the human and ecological effects of Hg, respectively. Biological Hg hotspots receive elevated atmospheric Hg deposition, have high landscape sensitivity, and/or experience large reservoir fluctuations. In the Merrimack River watershed, local Hg emissions are linked to elevated local deposition and high Hg concentrations in biota. Time series data for this region suggest that reductions in Hg emissions from local sources can lead to rapid reductions of Hg in biota. An enhanced Hg monitoring network is needed to further document areas of high deposition, biological hotspots, and the response to emissions reductions and other mitigation strategies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".