Dive Behavior of Eastern Chukchi Beluga Whales (<i>Delphinapterus leucas</i>), 1998–2008
Bibliographic record
Abstract
We provide an exploratory description of the dive behavior of 23 beluga whales of the eastern Chukchi Sea stock, tagged with satellite-linked time and depth recorders at Point Lay, Alaska, between 1998 and 2007. Because of differences in how transmitters were parameterized, we analyzed data from tags deployed from 1998 to 2002 (n = 20 tags) and data from tags deployed in 2007 (n = 3 tags) separately. Using cluster analysis, we found three basic dive types in the 1998–2002 dataset. “Shallow” diving behavior was characterized by dives mostly 50 m in depth. “Intermediate” diving behavior was characterized by having one mode near the surface and a second mode near 250 m. “Deep” diving behavior was characterized by having one mode near the surface and a second mode more than 400 m from the surface. The average number of dives per hour ranged from 5.1 (SD = 2.1) to 9.8 (SD = 2.9) across dive types, with the fewest dives per hour in the deep diving category. In general, duration of dives ranged from 1 to 18 minutes; however, dives up to 21 minutes occurred in the deepest diving category. We found little evidence that dive behavior of the belugas in our sample varied by sex or age. In general, belugas dove more deeply in the eastern Beaufort Sea than in the western Beaufort or Chukchi Seas. The depths to which belugas most commonly dive in Barrow Canyon and along the Beaufort shelf break (200–300 m) correspond to the boundary where colder Pacific water overlies warmer Atlantic water, which is probably where Arctic cod (Boreogadus saida) are most dense. Diving depths within the Arctic Basin suggest that belugas are foraging mostly within the warm layer of Atlantic Water (~200–1000 m).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".