Mercury exposure and reproduction in fish-eating birds breeding in the Pinchi Lake region, British Columbia, Canada
Bibliographic record
Abstract
To determine whether Hg from geologic/mining-related sources at Pinchi Lake (BC, Canada) was causing elevated Hg exposure and/or adversely affecting reproduction in fish-eating birds, breeding bald eagles (Haliaeetus leucocephalus) on Pinchi Lake and four nearby reference lakes were sampled for blood and feather Hg concentrations and monitored for reproductive success during the summers of 2000, 2001, and 2002. Eggs of red-necked grebes (Podiceps grisgena) also were collected and analyzed. Mercury levels in species at various trophic levels from Pinchi Lake averaged approximately twice those in the same species from nearby lakes combined, even in the absence of substantial new inputs of Hg to Pinchi Lake over several decades. In Pinchi Lake, Hg concentrations in blood and feathers of eagles and eggs of grebes were significantly higher than those in corresponding samples from reference lakes. However, the mean Hg concentration (0.25 microg/g wet wt) in grebe eggs from Pinchi Lake was substantially lower than accepted threshold levels for reproductive toxicity in most avian species (0.5-1.0 microg/g wet wt). Mercury concentrations in the blood of adult eagles and their chicks were highly correlated (r = 0.91, p = 0.004). Despite elevated Hg exposure in adult eagles nesting on Pinchi Lake (blood Hg concentration, 4.3-9.4 microg/ml), birds appeared to be in good body condition, did not differ significantly in terms of weight from eagles nesting on reference lakes, and exhibited no evidence of obvious abnormal behavior or lack of coordination. Eagle reproductive success and productivity on Pinchi Lake were not significantly different from those on all reference lakes combined (p = 0.483).
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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 | 0.001 | 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) | 0.002 | 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 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".