The Arctic underwater soundscape today and as projected for 2030
Bibliographic record
Abstract
Canada, the United States, and the World Wildlife Fund are co-sponsoring ongoing work in the Arctic Council’s Protection for the Marine Environment Working Group to evaluate shipping noise in the Arctic region. Applied Ocean Sciences has used ship tracking and sea ice data to model the region’s underwater soundscape to improve understanding of radiated noise generated by shipping throughout the PanArctic. Current (2019) models have been compared with ambient noise measurements collected during time periods when vessel sounds were identifiably present and when biological sounds were not. Projections of ice cover and shipping routes along and between the northern borders of Arctic countries were used to forecast potential future (2030) Arctic soundscapes. Focused interpretation of these model results within sub-regions, time periods, and frequencies important to marine fauna and in turn to indigenous peoples will be provided to PAME and other fora seeking to guide the development of shipping practices and mitigation strategies. The final results will be incorporated as a PAME/Arctic Council product. This presentation will focus on the acoustic modeling work under projected sea ice conditions, maps of “excess noise” induced by ships in 2019 and 2030, and risk assessment for a few endemic marine mammal species.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".