Population Genetics of Bowhead Whales (<i>Baleana mysticetus</i>) in the Western Arctic
Bibliographic record
Abstract
Bowhead whales (Balaena mysticetus) in the Bering, Chukchi, and Beaufort seas experienced a severe reduction as a result of commercial whaling in the 19th century. Since the cessation of commercial whaling, the population has recovered to a size that is approaching pre-whaling estimates. Inupiat and Yupik communities in northern and western Alaska hunt these Western Arctic (WA) bowheads along their migratory path during spring and fall. This hunting is regulated by the International Whaling Commission. Recent but preliminary analysis of available genetic data (207 whales and 10 microsatellite markers) raised the question of the presence of multiple, genetically distinct populations within the WA bowheads. Here we re-examined this question on the basis of a study of 414 whales and 22 newly developed microsatellite loci. We identified widespread departures from Hardy-Weinberg equilibrium; however, we were unable to detect significant evidence of multiple genetic populations within the WA bowheads that could explain this Hardy-Weinberg disequilibrium, particularly when compared to the strength of evidence for differentiation between WA bowheads and other populations from distant regions such as the Okhotsk Sea and eastern Canada. There was conclusive evidence of genetic differentiation among the three regions. The statistical rejection of panmixia within the WA improves our understanding of bowhead whale biology, and the lack of evidence for multiple populations within the WA enables risk-averse management of aboriginal hunting of Western Arctic bowhead whales.
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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 | 0.000 | 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 | 0.000 | 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 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".