Using passive acoustic monitoring to document the distribution of beaked whale species in the western North Atlantic Ocean
Bibliographic record
Abstract
Little is known about the ecology of many beaked whale species, despite concerns raised by mass strandings linked to certain sources of anthropogenic noise. Here, we used passive acoustic monitoring to examine spatial and temporal patterns in beaked whale occurrence at six locations along the continental slope in the western North Atlantic Ocean. We analyzed 2642 days of recordings collected between 2011 and 2015, and identified echolocation signals from northern bottlenose whales (Hyperoodon ampullatus), Cuvier’s (Ziphius cavirostris), Sowerby’s (Mesoplodon bidens), Gervais’, (Mesoplodon europaeus), and Blainville’s (Mesoplodon densirostris) beaked whales, and one signal type of unknown origin. We recorded multiple species at each site, with detections generally occurring year-round, and observed latitudinal gradients and site-specific variation in relative species occurrence. Notably, we regularly detected Cuvier’s beaked whales in a region where they have not been commonly observed, and discovered potential habitat partitioning among Cuvier’s and Gervais’ beaked whales within their overlapping ranges. This information on the distribution and seasonal occurrence of North Atlantic beaked whale species offers new insight into patterns of habitat use, and provides a year-round baseline from which to assess potential anthropogenic impacts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".