Passive acoustic monitoring and ambient noise in the high Arctic: Resolute Bay, Nunavut
Bibliographic record
Abstract
Resolute Bay, a remote bay in the Canadian High Arctic to the north of Parry Channel, hosts diverse populations of marine mammals that migrate through the bay each year following food availability and/or oceanographic conditions. The changing climate combined with increasing anthropogenic activity in the Arctic make it important to create an ecosystem baseline from which to predict, understand, and monitor future changes. Passive underwater acoustic observations provide a non-invasive way to monitor marine mammal presence. Broadband noise (10 Hz to 48 kHz) was recorded by an Autonomous Marine Acoustic Recorder (AMAR) and marine mammal click detections were logged by two CPODs over a 5 month period from August to December 2013. Acoustic data were processed with click and tonal call detectors to determine marine mammal presence. Resolute Bay is ice-covered 10 months a year, leading to increased broadband ambient noise levels due to ice movement. During the short open-water period, vessel activity is common in the bay. The aim is to compare these two different ambient noise regimes and how they affect the effectiveness of passive acoustic marine mammal detections and tracking.
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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 | 0.001 | 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".