Mercury dynamics from pan-Canadian survey of lakes: analyses of sediment cores
Bibliographic record
Abstract
Strong measures have been taken since the 1970s to reduce mercury emissions in Canada. However, long-range transport of emissions continues and constitutes a large percentage of the total anthropogenic deposition of mercury in Canada. Natural sources of mercury are also heterogeneously distributed across the Canadian landscape. As part of the LakePulse network (www.lakepulse.ca), we are quantifying mercury concentration in hundreds of lake sediment cores across 13 Canadian ecozones. Analyses from eastern Canada lakes showed that total mercury is significantly different among ecozones, and many ecozones showed higher total mercury concentrations in contemporary sediments. Contemporary methyl mercury concentrations also differed among ecozones. Our overarching goals are to map the heterogeneity in mercury concentrations across the country and to identify the most parsimonious set of predictors considering a suite of physico-chemical and land-use variables from lakes and their watersheds set across the temperate to subarctic landscape.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".