Mercury and marine birds in Arctic Canada: effects, current trends, and why we should be paying closer attention
Bibliographic record
Abstract
Mercury (Hg) is a naturally occurring trace element that is also a by-product of anthropogenic activities and, in its methylated form, it is a neurotoxin that can have adverse effects on wildlife. The toxicity of Hg for humans, wildlife, and ecosystem health merits monitoring of its concentrations by various sampling means. Marine birds are widely used as indicators of ecosystem health, including biomonitoring of Hg in the Arctic. Since the mid-1970s, Hg concentrations in marine birds have been monitored across the Canadian North. Current Hg burdens in most northern marine bird species are below levels associated with health concerns, but several species have concentrations that are at or near levels associated with impaired reproduction. Arctic marine birds in Canada may be particularly at risk from increasing Hg levels associated with changing climatic conditions and long-term Hg deposition patterns. Research on marine birds should, therefore, continue to focus on spatial and temporal patterns of Hg contamination, assessing levels and biological effects in species that are experiencing high concentrations, and among species that are widely harvested due to the possible implications for human health.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".