Changes in Mercury Levels in Great Lakes Fish Between 1970s and 2007
Bibliographic record
Abstract
A number of initiatives have curtailed anthropogenic mercury emissions in North America over the last two decades; however, various factors, including long-range transport of global emissions, may complicate the response of fish mercury levels to remedial actions. Since the Great Lakes of North America are together the largest surface freshwater body in the world and are under the influence of many complicating factors, trends of mercury in fish from the Great Lakes can reflect the overall impact of mercury management actions at local, regional, and perhaps global scales. Here we present a comprehensive view of mercury trends in Canadian Great Lakes fish using two large (total 5807 samples), different (fillet and whole fish), and long-term (1970s-2007) monitoring data sets. The spatial differences in lake trout and walleye mercury levels during this period have generally been within a factor of 2-3 with Lakes Erie and Superior having the lowest and highest concentrations, respectively. These spatial differences have diminished in the recent years (2000-2007). The concentrations have generally declined over the three decades (mid-1970s to 2007); however, in recent years, the concentration trends are flat in Lake Ontario walleye and appear to be increasing in Lake Erie walleye. There was a mismatch in the Lake Ontario lake trout and walleye temporal trends, which shows the importance of considering more than one fish species for proper spatial/temporal trend assessments.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".