Mercury Speciation in Piscivorous Fish from Mining-Impacted Reservoirs
Bibliographic record
Abstract
Guadalupe Reservoir (GUA), California, and Lahontan Reservoir (LAH), Nevada, U.S. are both affected either directly or indirectly by the legacy of gold and silver mining in the Sierra Nevada during the nineteenth century. Analysis of total mercury in fish from these lentic systems consistently indicate elevated concentrations (>1 microg x g(-1) wet weight; hereinafter, all concentrations are reported as wet weight unless indicated otherwise) well above the U.S. Environmenal Protection Agency's human consumption advisory level for fish (<0.3 microg x g(-1)). Replicate X-ray absorption near edge structure (XANES) analyses on largemouth bass and hybrid striped bass from GUA and LAH were performed to determine predominant chemical species of mercury accumulated by these high-trophic-level piscivores that are exposed to elevated mercury through trophic transfer in mining-impacted lentic systems. Despite distinct differences in mercury source, the proximity of the source, and concentrations of complexing ligands, results of XANES analysis clearly indicated that mercury accumulated in these individual fish from the two reservoirs were dominated by methylmercury cysteine complexes. These findings are consistent with results from commercial fish species inhabiting marine environments which are presumed to include differing mercury sources (e.g., atmospheric, hydrothermal, or benthic). The dominance of methylmercury cysteine complexes in muscle tissues of fish obtained from such contrasting environments and exposure conditions suggests that a generic toxicological model for the consumption of fish could be applicable over a wide range of ecologic settings.
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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 | 0.000 |
| 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".