Increasing Mercury in Yellow Perch at a Hotspot in Atlantic Canada, Kejimkujik National Park
Bibliographic record
Abstract
In the mid-1990s, yellow perch (Perca flavescens) and common loons (Gavia immer) from Kejimkujik National Park and National Historic Site (KNPNHS), Nova Scotia, Canada, had among the highest mercury (Hg) concentrations across North America. In 2006 and 2007, we re-examined 16 lakes to determine whether there have been changes in Hg in the loon's preferred prey, yellow perch. Total Hg concentrations were measured in up to nine perch in each of three size classes (5-10 cm, 10-15 cm, and 15-20 cm) consumed by loons. Between 1996/97 and 2006/07, polynomial regressions indicated that Hg in yellow perch increased an average of 29% in ten lakes, decreased an average of 21% in three, and were unchanged in the remaining three lakes. In 2006/07, perch in 75% of the study lakes had Hg concentrations (standardized to 12-cm fish length) equal to or above the concentration (0.21 μg·g(-1) ww) associated with a 50% reduction in maximum productivity of loons, compared with only 56% of these lakes in 1996/97. Mercury contamination currently poses a greater threat to loon health than a decade ago, and further reductions in anthropogenic emissions should be considered to reduce its impacts on ecosystem health.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".