Interactions between Leatherback Turtles and Killer Whales in Namibian Waters, Including Possible Predation
Bibliographic record
Abstract
Killer whales and leatherback turtles are infrequently sighted in the coastal waters of southern Africa. Year round observations in Walvis Bay, Namibia of killer whales (2003–2010) by multiple marine tour operators and opportunistic seasonal observations of leatherback turtles made during a cetacean research project in the area (2008–2010) have been collated. Visits to coastal waters by killer whales (n = 16) are sporadic and unpredictable but are slightly higher (n = 11) between late winter (August) and late summer (March). Leatherback turtles were only seen in the warmer periods of summer months (February–March) when the surface waters exceeded 15°C. Two interactions (one harassment and one probably predation) between killer whales and leatherback turtles have been recorded in Walvis Bay. This is the first report of killer whales eating leatherback turtles in the South Atlantic. These observations are noteworthy due to the low frequency of encounters of both species in the area, suggesting predation of turtles may be relatively common. Knowledge of the diet of killer whales is valuable due to the importance of dietary specialization in definition of ecotypes of the species.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".