Mercury Elimination by a Top Predator, <i>Esox lucius</i>
Bibliographic record
Abstract
Top-level piscivores are highly sought after for consumption in freshwater fisheries, yet these species contain the highest levels of the neurotoxin monomethylmercury (MMHg) and therefore present the greatest concern for MMHg exposure to humans. The slow elimination of MMHg is one factor that contributes to high levels of this contaminant in fish; however, little quantitative information exists on elimination rates by top predators in nature. We determined rates of MMHg elimination in northern pike (Esox lucius) by transferring fish that had naturally accumulated isotope-enriched MMHg (spike MMHg) through a whole-lake Hg loading study to a different lake. Over a period of ~7 y, pike were periodically recaptured and a small amount of muscle tissue was extracted using a nonlethal biopsy. Spike total mercury (THg) persisted in muscle tissue throughout the entire study despite discontinuing exposure upon transfer to the new lake. Spike THg burdens increased for the first ~460 d, followed by a decline to 65% of original burden levels over the next 200 d, and subsequently reached a plateau near original burden levels for the remainder of the study. We estimated the half-life of muscle THg to be 3.3 y (1193 d), roughly 1.2- to 2.7-fold slower than predicted by current elimination models. We advocate for further long-term field studies that examine kinetics of MMHg in fish to better inform predictive models estimating the recovery of MMHg-contaminated fisheries.
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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 | 0.000 | 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) | 0.001 | 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".