Tracking fin whales in a coastal fjord using passive acoustics
Bibliographic record
Abstract
In the north-eastern Pacific, fin whales (Balaenoptara physalus) are typically found and studied in open waters near or seaward of the continental shelf. The Kitimat fjord system is a network of sounds and channels along the coast of British Columbia, Canada, and is one of only a few known fin whale habitats within confined coastal waters. In 2018, we deployed a network of hydrophones in Squally Channel, a proposed shipping lane located at the center of the fjord system, to monitor and track fin whales for a period of 2 years. The work is part of an effort to mitigate anthropogenic stressors on whales in the traditional territory of the Gitga'at First Nation. Here, we present spatial-temporal habitat use by fin whales in this confined inshore ecosystem based on more than 30 000 call detections and 7000 source localizations. Two distinct call types were recorded, a 20 Hz and a 40 Hz pulse, with distinctly different seasonal and diel trends. About 100 individual tracks were reconstructed from 20 Hz call sequences and analyzed for calling characteristics and movement patterns. A better understanding of fin whale habitat in the north-east Pacific is of special importance in light of an active discussion about the conservation status of this large baleen whale in Canadian waters.
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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 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".