Echolocation click characteristics of two fish-eating killer whale populations
Bibliographic record
Abstract
Acoustic disturbance has been identified as a threat to the survival of the endangered Southern Resident killer whale (SRKW) population whose critical habitat in the Salish Sea overlaps with busy commercial shipping lanes and popular recreational boating areas. Vessel noise has the potential to mask important sounds used by the whales for navigating, communicating, and foraging. To investigate the impact on foraging, acoustic characteristics of the whales’ echolocation clicks must be known. We collected data on SRKW in the wild using a 2 × 2 m2 23-hydrophone array deployed at short ranges (<500 m). We also acquired data on a neighboring population of Northern Resident killer whales (NRKW), whose numbers are increasing. Comparable results were obtained for most parameters between the two populations. Average peak-to-peak apparent source levels were 203 and 196 dB re 1 μPa at 1 m for SRKW and NRKW, respectively. The two populations had similar mean centroid and peak frequencies ranging between 26–29 kHz and 19–21 kHz, respectively. However, root-mean-square bandwidths differed significantly between the populations, with averages of 52 and 39 kHz for SRKWs and NRKWs, respectively. These results will be used to investigate masking potential under varying ambient noise conditions.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".