Bibliographic record
Abstract
Harvest reporting has been in place for High Arctic muskoxen in Nunavut, Canada, since 1990-91. The communities of Resolute, Grise Fiord, and Arctic Bay harvest muskoxen in the region. Overall, muskox harvest has declined in Resolute and Grise Fiord since the 1990s. The recovery of Peary caribou populations on the Bathurst Island Complex, which provides an alternate preferred source of country food, may be a factor behind Resolute’s decreased muskox harvest. The proportion of harvest for domestic use has also declined relative to sport hunts, which have remained relatively constant since the 1990s. We compared muskox harvest from tag records and reported harvest, i.e., the voluntary surveys to the Nunavut Wildlife Harvest Study for muskoxen. It is clear that voluntarily reported harvest underestimates actual harvest, but not consistently enough to predict the actual harvest. Muskox populations are at historic high levels on Bathurst Island, southern Ellesmere Island, and Devon Island and could support more harvest than is currently taken. Changes to Total Allowable Harvests and management unit boundaries in 2015, combined with a decline in the availability of Baffin Island caribou as country food, may result in increased harvest pressure on muskoxen in the High Arctic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".