Use of a novel acoustic ‘listening’ method for detecting pump impellor strike on downstream migrating eels
Bibliographic record
Abstract
Fish mortality through floodplain pumping stations is a recognised global issue, but few studies have quantified the degree of mortality that occurs during pumping. We investigated the potential of passive acoustic monitoring (PAM) as a tool to record sounds made by fish and their likely mortality as they passed through pumps during downstream migration. The acoustic properties made by freshly killed eels that were fed through an existing pump station were compared to those made by goldfish (Carassius auratus). Processing and analysis of acoustic data enabled the development of an ‘eel-specific’ algorithm for detecting eels passing through the pumping station. The duration of sound and filtered intensity were useful characteristics enabling reliable separation of the two fish species. The algorithm was then applied retrospectively to soundscape recordings obtained during a typical eel migration period at the test site. Although the tool is unlikely to be able to differentiate the sound of goldfish from ‘other’ potential sounds of short duration (e.g. sticks), differentiating eels from other sounds was demonstrated. We conclude that this tool has considerable potential for improving the understanding of the timing of eel migrations and likely mortality through pumping stations. The tool may also be used to inform the development of both remote and manual pump management options for reducing pump-related eel mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".