Marine Mammal Vocalisations in the High Arctic: Resolute Bay, Nunavut
Bibliographic record
Abstract
Resolute Bay is located in the Canadian Arctic Archipelago, on the southwest side of Cornwallis Island, with its waters facing the northern part of Parry Channel. During its short 2-month ice-free period each year, Resolute Bay hosts migratory groups of marine mammals. With the changing climate and increasing anthropogenic activity in the Arctic, it is important to study this sensitive ecosystem in order to predict, understand, and monitor future changes. An Autonomous Marine Acoustic Recorder (AMAR) was deployed in the bay at a depth of 43 m and collected broadband (10 Hz to 48 kHz) underwater sound for 2 months between August and October 2013, in order to capture the vocalisations of the migrating marine mammals. Subsequently, a smaller broadband range (10 Hz to 8 kHz) was recorded between October 2013 and July 2014 to capture ambient noise and seal and walrus vocalisations. These data were processed using two different automatic marine mammal vocalisation detectors. First, a tonal call detector was used to find whistles from whales, as well as bearded seal and walrus vocalizations. Then a click detector was used to find clicks from narwhals and belugas. The data from the acoustic recorder and the marine mammal click detectors were analyzed to determine the temporal variability of vocalising marine species in Resolute Bay. All species vocalised at all times of the day, with most clicks present at the end of September, right before freeze-up. Beluga and Narwhal whistles were present throughout the recording period, but predominantly at the beginning and end of September. Bearded seal calls occurred mostly at the end of June and at the end of September, with a handful of calls during the winter. The greatest amount of walrus grunts were recorded at the beginning of October.
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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 | 0.001 |
| 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".