Evidence of killer whale predation on a yearling bowhead whale in Cumberland Sound, Nunavut
Bibliographic record
Abstract
Accounts of killer whale (Orcinus orca) predation on marine mammals in the Canadian Arctic are relatively uncommon. Although second-hand reports of killer whale predation events in the Arctic are more common in recent years, these observations are generally poorly documented and the outcome of attacks are often unknown. On 12 August 2016, a floating bowhead whale (Balaena mysticetus) carcass was found off-shore in Cumberland Sound, Nunavut — presumably predated by killer whales that were sighted in the area. Inspection of the carcass revealed injuries consistent with published accounts of killer whale predation on large whales and observations of killer whale predation on bowheads described in Inuit traditional knowledge. The bowhead was male, 6.1 m long in good nutritional condition and estimated between 14 and 16 months old. As a recently weaned yearling, this whale would have been highly vulnerable to killer whale predation. With decreasing summer sea ice making some areas of the Arctic more accessible, the incursion and presence of killer whales in the Arctic is expected to increase. A better understanding of Arctic killer whale predation pressure is needed to predict the potential impact they will have on the eastern Canada–west Greenland bowhead population as well as on other marine mammal prey.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".