Mercury concentrations in Double—crested Cormorant chicks across Canada
Bibliographic record
Abstract
Abstract Mercury (Hg) biomagnifies in aquatic food chains and can reach high concentrations in fish-eating birds. Spatial patterns of Hg have been found in freshwater ecosystems across Canada for many taxa including fish and birds. However, it is often challenging to sample a representative population size of adult birds to monitor concentrations of contaminants over a large spatial scale. Moreover, adult birds can migrate and can show a contaminant profile that may not be representative of local resources. The aims of this study were (1) to determine if there was a spatial pattern of Hg in piscivorous birds, (2) to develop a model to estimate Hg concentrations in breeding adults using chicks as proxy, and (3) to develop predictive equations among non-lethal samples that representative of local resources in adults (blood and growing feathers). Double-crested Cormorant ( Phalacrocorax auritus ) chick growing feathers were sampled at 19 sites across Canada ( n = 106). Adult tissues (freshly grown feathers; n = 8-16 per feather type and blood; n = 160) were sampled at five of those locations to establish correlations between age classes and between adult tissues. We found an increase in Hg concentrations with latitude up to 50°N followed by a decrease. There was a decrease in Hg concentrations from west to east, which contradicts previous studies. We found a good correlation of Hg concentrations between adults and chicks and among adult tissues. Our model showed that it is possible to estimate Hg concentrations in adults across Canada using chicks as proxy. Our study shows that chicks can be a suitable proxy for monitoring local mercury concentrations and that they are representative of adults. Capsule: Concentrations of mercury in cormorant chicks are influenced by latitude
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".