The effect of selenium on mercury assimilation by freshwater organisms
Bibliographic record
Abstract
In this study, we showed that selenium (Se) deposition from metal smelters in Sudbury, Ontario, greatly re duces the bioassimilation of mercury (Hg) by aquatic biota throughout the food web. Concentrations of total and methyl mercury in tissues of zooplankton, mayflies (Stenonema femoratum), amphipods (Hyalella azteca), and young-of-the-year perch (Perca flavescens) were positively correlated with increasing distance from Sudbury smelters and inversely correlated with Se concentrations in lake water. Although concentrations of total Hg and total Se in tissues showed weak or no correlation in most of the studied aquatic species, methyl mercury and total Se showed much clearer inverse trends. Similar to the results of our previous study of muscle tissue from adult perch and walleye (Sander vitreus), these findings suggest that Se plays an important role in limiting the whole-body assimilation of Hg at lower levels of the aquatic food chain. High Se concentrations may force a preferential assimilation of the element over Hg through a competitive adsorption on binding sites. They may also restrict the solubility and availability of Hg to aquatic organisms or reduce the methylation of this metal in lakes.
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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 | 0.001 |
| 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".