Assessing vessel slowdown for reducing auditory masking for marine mammals and fish of the western Canadian Arctic
Bibliographic record
Abstract
Vessel slowdown may be an alternative mitigation option in regions where re-routing shipping corridors to avoid important marine mammal habitat is not possible. We investigated the potential relief in masking in marine mammals and fish from a 10 knot speed reduction of container and cruise ships. The mitigation effect from slower vessels was not equal between ambient sound conditions, species or vessel-type. Under quiet ambient conditions, a speed reduction from 25 to 15 knots resulted in smaller listening space reductions by 16–23%, 10–18%, 1–2%, 5–8% and 8% respectively for belugas, bowheads, bearded seals, ringed seals, and fish, depending on vessel-type. However, under noisy conditions, those savings were between 9 and 19% more, depending on the species. This was due to the differences in species' hearing sensitivities and the low ambient sound levels measured in the study region. Vessel slowdown could be an effective mitigation strategy for reducing masking.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".