Seals in western Hudson Bay: Assessing proportions in natural and human harvests using genetic methods
Bibliographic record
Abstract
Arctic seals are of great importance to polar bears (Ursus maritimus) and humans, however the ecosystem that supports them is changing as the climate warms. In spite of the importance of seals, little is known about their abundance or the relative abundance of each species. The proportion of seals harvested by hunters and seals killed by polar bears could be used to infer the naturally occurring relative abundance in Hudson Bay. This study compares 104 seal samples harvested by hunters between 2014-2016 and 12 seal samples killed by polar bears in 2014. All samples are from Hudson Bay near Churchill, Manitoba. Analysis of the samples determined which species: harbour seal (Phoca vitulina), ringed seal (Pusa ispida), and bearded seal (Erignathus barbatus) are killed by polar bears and humans. I developed a restriction enzyme digest to determine the species of these samples, quickly and cheaply. I found that there was no difference (p=0.998, Freeman-Halton extension of the Fisher's exact test) between the proportion of seals harvested by humans or by polar bears, which suggests that both polar bears and humans are harvesting seals in the proportions with which they are encountered in this area. The data also provided insight into polar bear diet, in that they prefer ringed seals over bearded and harbour seals. Understanding predators and their prey in the Arctic is important as climate warming and changes occur in sea ice habitat that seals and polar bears rely on.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".