Hydroacoustic measurements of the behavioral response of arctic riverine fishes to seismic airguns
Bibliographic record
Abstract
Seismic surveys for hydrocarbon exploration in the Mackenzie River involve the use of airguns. Airguns produce a repetitive, intense, low-frequency sound that has the potential to cause physiological damage and behavioral changes in fishes. Some of these impacts have been documented in marine environments but few studies have been conducted in freshwater systems where the confining nature of the environment produces a different acoustic regime and could constrain possible fish response. In the current study, hydroacoustic surveys are conducted in the presence of airgun firing in the Mackenzie River to determine if fish behavior can mitigate or enhance the potential impact of this sound. It is shown that fish behavioral characteristics measured in this study are generally not changed by the presence of airgun noise. The most likely mechanism to facilitate a severe physiological effect in fishes from a mobile airgun firing is a herding response in front of the airgun, resulting in prolonged exposure to the noise. Analysis of tracked fish directional movement does not indicate that herding behavior occurs. Consequently, no evidence is found to indicate that fishes in this study would sustain severe physiological damage from this airgun seismic survey.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".