Seasonal patterns in marine mammal vocalizations in the western Canadian Arctic
Bibliographic record
Abstract
The Arctic marine environment is changing rapidly through a combination of sea ice loss and increased anthropogenic activity. Given that these changes can affect marine animals in a variety of ways, understanding the spatial and temporal distributions of Arctic marine animals is imperative. Here, we use passive acoustic monitoring to examine the presence of marine mammals in the western Canadian Arctic, where we have had recorders deployed near the communities of Sachs Harbour and Ulukhaktok, Northwest Territories, Canada. At both sites, we documented bowhead and beluga whales during the ice-free season, bearded seals throughout the ice-covered season and during their mating season, and ringed seals throughout the year. The sites also had different patterns in marine mammal presence, where we found whales later into the year at Ulukhaktok than at Sachs Harbour, and ringed seals vocalized much more at Ulukhaktok than at Sachs Harbour. These patterns in vocal activity at both sites help to document the presence of each species in the western Canadian Arctic, and serve as a baseline for future monitoring in the region. Next steps in this project involve deploying at more sites throughout the region to more comprehensively monitor marine mammals in the region.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".