Genetic assessment of beluga in Cumberland Sound
Bibliographic record
Abstract
Beluga whales in Cumberland Sound are harvested by hunters from the hamlet of Pangnirtung. Assessments in 2016 and 2019 indicated the current harvest is not sustainable. Harvest changes have not been implemented, in part, because there are questions regarding the number of beluga whale populations that inhabit Cumberland Sound. Genetic variation among beluga whales harvested in Cumberland Sound was assessed against samples from other Canadian populations using DNA inherited from both parents and from mothers only. Genetic analyses revealed that there is a distinct population specific to Cumberland Sound, hereafter identified as the Cumberland Sound Beluga (CSB) population. Whales harvested in Cumberland Sound comprise two populations. Of the 27 samples evaluated from DNA inherited from both parents, the majority were from the CSB population (74%). The remainder (26%) were most similar to whales from the Western Hudson Bay (WHB) population. It is unknown whether whales most similar to WHB were temporary or permanent migrants in Cumberland Sound. The frequency of possible migration is also unknown. Because these two populations cannot be distinguished visually during abundance surveys, management should recognize that the distinct CSB population is likely smaller than previously estimated. Future genetic assessments of beluga in Cumberland Sound would benefit from including DNA inherited from both parents.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".