Evidence of Weak Contaminant-Related Oxidative Stress in Glaucous Gulls (<i>Larus hyperboreus</i>) from the Canadian Arctic
Bibliographic record
Abstract
Environmental contaminants are transported over great distances to Arctic ecosystems, where they can accumulate in wildlife. Whether contaminant concentrations in wildlife are sufficient to produce adverse effects remains poorly understood. Exposure to contaminants elevates oxidative stress with possible fitness consequences. The glaucous gull (Larus hyperboreus), an Arctic top predator, was used as a bioindicator for investigating relationships between contaminant levels (organochlorines and polychlorinated biphenyls [OC/PCB], mercury [Hg], and selenium [Se]) and measures of oxidative stress (glutathione [GSH] metabolism and lipid peroxidation) in Canadian Arctic ecosystems. Contaminant levels were low and associations between contaminant exposure and oxidative stress were weak. Nevertheless, glutathione peroxidase activity rose with increasing hepatic Se concentrations, levels of thiols declined as Hg and OC/PCB levels rose, and at one of the two study sites levels of lipid peroxidation were elevated with increasing levels of hepatic Hg. These results suggest the possibility of a deleterious effect of exposure to contaminants on gull physiology even at low contaminant exposures.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".