Acoustic behavior of dolphins in the Pacific Ocean: Implications for using passive acoustic methods for population studies
Bibliographic record
Abstract
The Southwest Fisheries Science Center has been conducting shipboard visual line-transect cetacean surveys for over 30 years, and combined visual and acoustic surveys for seven years. Full incorporation of passive acoustics as a tool for population assessment requires an understanding of the acoustic behavior of cetaceans as well as the limitations of the methods used in these surveys. Our research summarizes data collected during seven years of combined visual and acoustic surveys throughout the central and eastern North Pacific Ocean, ranging from the Aleutian Island chain in the north, to Peru in the south. Phonations from 2.034 dolphin schools were examined to better understand the acoustic behavior of cetaceans. Equally important are the cetacean schools that were seen but not heard, and this analysis includes an examination of these groups by species, group size, geographic location, and time of day. The results of this analysis allow us to take the first steps to incorporate passive acoustics into line-transect cetacean surveys.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".