Real-time acoustic observations in the Canadian Arctic Archipelago
Bibliographic record
Abstract
The main sources of noise in the Arctic Ocean are naturally occurring, rather than related to human activities. Sustained acoustic monitoring at high latitudes provides quantitative measures of changes in the sound field attributable to evolving human activity or shifting environmental conditions. A 12-month ambient sound time series (September 2018 to August 2019) recorded and transmitted from a real-time monitoring station near Gascoyne Inlet, Nunavut is presented. During this time, sound levels in the band 16–6400 Hz ranged between 10 and 135 dB re 1 μPa2/Hz. The average monthly sound levels follow seasonal ice variations with a dependence on the timing of ice melt and freeze-up and with higher frequencies varying more strongly than the lower frequencies. Ambient sound levels are higher in the summer during open water and quietest in the winter during periods of pack ice and shore fast ice. An autocorrelation of monthly noise levels over the ice freeze-up and complete cover periods reveal a ∼24 h periodic trend in noise power at high frequencies (>1000 Hz) caused by tidally driven surface currents in combination with increased ice block collisions or increased stress in the shore fast sea ice.
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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 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| 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".