Antagonistic effect of selenium on mercury assimilation by fish populations near Sudbury metal smelters?
Bibliographic record
Abstract
In this study, the concentrations of Se and Hg were determined in perch ( Perca flavescens ) and walleye ( Stizosedion vitreum ) muscle from nine lakes that varied in distance (4–204 km) from the metal smelters of Sudbury, Canada. Significant inverse relationships between Se and Hg in perch (r 2 = 0.79, P < 0.05) and walleye tissue (r 2 = 0.97, P < 0.01) were detected, which suggests a strong antagonistic effect of Se on Hg assimilation by these fish species. Concentration of Hg decreased exponentially with an increase of Se in fish muscle. Total dissolved Se concentrations of lake water declined with distance from smelters and were correlated to Se in perch (r 2 = 0.75, P < 0.05) and walleye (r 2 = 0.95, P < 0.01). Hg concentrations in the fish from lakes near the smelter were well below average values in fish in boreal shield lakes of this region.
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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) | 0.000 | 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 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".