A Forensic Evaluation: the use of Mercury and Stable Isotope analysis of Museum Bone Samples to Monitor if Environmental Changes are affecting the Eating Patterns of Red and Arctic Foxes
Bibliographic record
Abstract
Global climate changes can potentially impact the ecosystems of the red foxes (Vulpes vulpes) and Arctic foxes (Alopex lagopus) on a regional scale. This research takes a forensic approach at investigating certain health and dietary indicators in museum preserved bone of red foxes of Bethel Alaska and Arctic foxes from the Yukon Territory in Canada. This study attempts to 1) measure the mercury (THg) concentration levels, 2) estimate a diet using carbon stable isotopes (δ13C) and 3) establish a trophic level using nitrogen stable isotopes (δ15N), from bones of these sentinel species. This study examines two Arctic foxes and three red foxes of unknown age and origin. The Yukon Territory Arctic foxes bone THg concentrations were 0.017 and 0.025 mg/kg. The red foxes bone THg concentrations were 0.010, 0.036 and 0.073 mg/kg. The δ13C levels were -21.13 and -21.36‰ for Arctic foxes and -20.05, -20.08, and -23.12‰ for red foxes. Their δ15N levels were 5.59 and 7.22‰ for the Arctic foxes and 6.10, 6.57 and 6.66‰ for red foxes. These Arctic and red Yukon Territory foxes indicate a trophic level similar to Arctic terrestrial omnivores. This type of forensic study is useful to establish past ecosystems of the Arctic. In understanding past ecosystems we can then monitor the effects of climate change and its impact on human health and the health of terrestrial animals.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".