Life history and population dynamics of southern Alaska resident killer whales (<i>Orcinus orca</i>)
Bibliographic record
Abstract
Abstract Resident (fish eating) killer whales (Orcinus orca ) in the North Pacific have been the subject of long‐term studies in several geographical regions. The current study examines population parameters in the southern Alaska resident population from 1984 to 2010 and develops a population model. The southern Alaska resident population ranges from southeastern Alaska through the Kodiak archipelago and contains over 700 individuals. We follow the life histories of 343 identifiable whales in 10 pods from two clans born before and during the study. Population parameters were comparable to those of the British Columbia northern resident population during the 1970s and 1980s, except that age of maturity was approximately one year earlier. The average annual rate of increase was slightly higher in Alaska (3.5%) than for the British Columbia northern residents (2.9%) and probably represents a population at r‐max (maximum rate of growth). Reasons for the high growth rate in Alaska could be a recovery following past anthropogenic mortalities, or more likely, a response to increasing salmon returns in recent decades, resulting in an increase in carrying capacity. The slow maturation and low rate of reproductive response makes these whales slow to recover from natural or anthropogenic catastrophes.
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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 | 0.000 | 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 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".