Acoustic detections of Arctic marine mammals near Ulukhaktok, Northwest Territories, Canada
Bibliographic record
Abstract
The Arctic marine environment is changing rapidly through a combination of sea ice loss and increased anthropogenic activity. Given these changes can affect marine animals in a variety of ways, understanding the spatial and temporal distributions of Arctic marine animals is imperative. We use passive acoustic monitoring to examine the presence of marine mammals near Ulukhaktok, Northwest Territories, Canada, from October 2016 to April 2017. We documented bowhead whale (Balaena mysticetus Linnaeus, 1758) and beluga whale (Delphinapterus leucas (Pallas, 1776)) vocalizations later into the autumn than expected, and we recorded bowhead whales in early April. We recorded ringed seal (Pusa hispida (Schreber, 1775)) vocalizations throughout our deployment, with higher vocal activity than in other studies and with peak vocal activity in January. We recorded bearded seals (Erignathus barbatus (Erxleben, 1777)) throughout the deployment, with peak vocal activity in February. We recorded lower bearded seal vocal activity than other studies, and almost no vocal activity near the beginning of the spring breeding season. Both seal species vocalized more when ice concentration was high. These patterns in vocal activity document the presence of each species at this site over autumn and winter and are a useful comparison for future monitoring.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".