Behavioral responses of <i>Chinook salmon</i> to shipping noise in Cowichan Bay, British Columbia
Bibliographic record
Abstract
The increase in human-generated noise over the last 60 years has led to concerns regarding the impacts of shipping noise on marine species. Two important species in the northeast Pacific are declining, southern resident killer whales and their main prey, Chinook salmon. We know that killer whales change their behavior in the presence of ships, but no work has been done on salmon. Acoustic receivers and underwater hydrophones were deployed in Cowichan Bay, British Columbia, Canada, to understand potential changes in behavior as salmon encounter shipping noise. Depth and acceleration of adult Chinook salmon were monitored using acoustic tags and were modeled against environmental conditions (e.g., currents) to understand general movement and behavior. Underwater sound pressure levels were then added to the model to assess potential responses to ship noise. Over 3 years, 53 Chinook salmon were tagged, resulting in 167,628 individual detections. Detections revealed spatial and temporal patterns in habitat use and behavior prior to river entry and provided the first data on Chinook salmon responses to anthropogenic noise. These data provide novel insights into the behavior of adult Chinook salmon and crucial information on the impacts of anthropogenic noise on this key 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".