Calling depth and time and frequency attributes of harp (<i>Pagophilus groenlandicus</i>) and Weddell (<i>Leptonychotes weddellii</i>) seal underwater vocalizations
Bibliographic record
Abstract
Harp seal (Pagophilus groenlandicus (Erxleben, 1777)) daytime calling depth during the breeding season and Weddell seal (Leptonychotes weddellii (Lesson, 1826)) daytime and nighttime calling depth during the winter and breeding seasons were investigated using a small vertical array with hydrophones placed at depths of 10 and 60 m. Rough calling depth estimates (<35 m, ~35 m, >35 m) and more accurate point depth estimates (±5–10 m in most cases) were obtained. Significantly more calls were produced at depths ≤35 m for both species. The point depth estimates indicated that the calls occurred most frequently at depths >10 m; 60% of harp seal calls and 71% of Weddell seal calls occurred at depths between 10 and 35 m. The seals called predominately within areas of the water column where light would likely penetrate, but still avoided sea-ice interference to some extent. The vocalizations did not change over depth with respect to call type, the number of elements within a call, or total call duration, or with respect to season and light condition for Weddell seals. Frequency (kHz) of calls also did not change with depth, suggesting that harp and Weddell seals control the pitch of their vocalizations with the vocal cords of the larynx.
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 | 0.000 | 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".