Vocal repertoire and acoustic behavior of the isolated AT1 killer whale subpopulation in southern Alaska
Bibliographic record
Abstract
Killer whales, Orcinus orca (L., 1758), in the North Pacific are classified as three genetically distinct ecotypes: residents (fish-eaters), transients (mammal-eaters), and offshores (probable fish-eaters). Within the transient ecotype, three putative subpopulations have been identified by genetic analysis: West Coast transients, Gulf of Alaska transients, and AT1 transients. Here, we examine the behavior and vocalizations of the AT1 transients, which are found only in the Prince William Sound/Kenai Fjords region, to determine if their acoustic behavior distinguishes them from other genetically distinct transient subpopulations. We identified 14 discrete, pulsed calls in the vocal repertoire of the AT1 transients. These calls were entirely different than those of West Coast and sympatric Gulf of Alaska transients. Despite their large call repertoire, AT1 transients were silent most of the time, utilizing a foraging strategy of stealth, acoustic crypsis, and passive listening for locating marine-mammal prey. Unlike resident killer whales, AT1 transient vocalization types were context specific. For example, lone AT1 transients produced long-distance, high-amplitude pulsed calls in stereotyped sequences to locate other AT1 whales. In contrast, hunting individuals emitted low-amplitude pulsed calls to maintain contact with group members. The repertoire and call-usage patterns of the AT1 transients are consistent with genetic evidence that they are a unique, reproductively and socially isolated subpopulation in danger of extinction.
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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 | 0.000 |
| 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".