An overview of mercury concentrations in freshwater fish species: a national fish mercury dataset for Canada
Bibliographic record
Abstract
Fish mercury (Hg) concentrations have been measured over the last 30–40 years in all regions of Canada as part of various monitoring and research programs. Despite this large amount of data, only regional assessments of fish Hg trends and patterns have previously been attempted. The objective of this study was to assemble available freshwater fish Hg concentration data from all provinces and territories and identify national patterns. The Canadian Fish Mercury Database includes over 330 000 records representing 104 species of freshwater fish collected from over 5000 locations across Canada between 1967 and 2010. Analysis of the 28 most frequently occurring species (>1000 records) showed that the majority of variation in Hg concentrations (when normalized to a standard size) was accounted for by geographic location. Median Hg concentrations increased with trophic level (r = 0.40, p < 0.05), with the highest Hg concentrations found in piscivorous species such as walleye (Sander vitreus), northern pike (Esox lucius), and lake trout (Salvelinus namaycush). The Canadian Fish Mercury Database provides the most comprehensive summary of fish Hg measurements in Canada, and the results indicate that several regionally observed trends in fish Hg concentrations (e.g., Hg biomagnification and geographic variation) are observed at a national scale. Implications for the effective assessment of changes in fish Hg concentrations in relation to changes in Hg emission regulations are discussed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.023 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".