Dive and surfacing characteristics of bowhead whales (<i>Balaena mysticetus</i>) in the Beaufort and Chukchi seas
Bibliographic record
Abstract
We received data from eight bowhead whales (Balaena mysticetus) equipped with satellite-monitored radio tags for 3-33 days. Of 42 306 dives made by the eight whales during 1695 h, 9573 were sounding dives (>1 min duration). The mean duration of sounding dives for individuals varied from 6.9 to 14.1 min (mean = 10.4 ± 2.4 min, n = 8). Five whales made dives [Formula: see text]61 min; the longest dives for the other three lasted 56, 45, and 32 min. Five tags measured maximum depths of 29 499 dives during 1220 h and time at depth during 1228 h. All five whales dived >100 m; the deepest dive was 352 m. Whales spent most of their time at depths [Formula: see text]16 m, but three whales spent most of their time at depths >48 m during some sampling periods. Mean surfacing rates ranged from 18.2 to 47.0/h (mean = 26.2 ± 9.0/h, n = 8). Tags were exposed to air for 4.0-7.3% of the time (mean = 5.5 ± 0.95%, n = 8), and whales were potentially visible from aircraft for 8.5-16.4% of the time (mean = 11.1 ± 2.4%, n = 8). Three whales made longer sounding dives and had lower surfacing rates when in [Formula: see text]90% ice cover. No consistent diel patterns were found.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".