Passive acoustic monitoring to identify drivers of beluga whale habitat use in the Mackenzie Estuary
Bibliographic record
Abstract
Understanding drivers of habitat use of mobile species is critical for understanding the impacts of climate change and formulating management plans. Eastern Beaufort Sea (EBS) beluga whales (Delphinapterus leucas), an important subsistence food source for Inuvialuit, are known to form large aggregations in the Mackenzie Estuary each summer; however, environmental drivers of this habitat use are not understood. Passive acoustic monitoring was used to record beluga presence during this aggregation at key locations in the Mackenzie Estuary, while simultaneously recording environmental and oceanographic data. Belugas moved further into the estuary during cold oceanic influxes and did not use locations which typically see high use during high-speed winds. In an extreme case, a large storm prevented belugas from using the area for five days and negatively affected the subsistence beluga hunt. This information can inform decisions by northern communities and policy makers, aiding in management of the EBS beluga population.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".