Assessment of sound attenuation by submerged aquatic vegetation in shallow freshwaters
Bibliographic record
Abstract
Acoustic propagation measurements were conducted in the shallow freshwater of Lake St. Pierre, a widening of the St. Lawrence River between Montréal and Trois-Rivières. Two (2) calibrated acoustic projectors were used to cover a mid-to-high frequency range between 2-60 . Sites across the lake were selected to span a broad gradient of submerged aquatic vegetation (SAV) density, estimated semi-quantitatively through effective percent cover, to evaluate its impact on sound attenuation. Vegetation-induced excess propagation loss over 10 ranged from near 0 re 1 at sparsely vegetated sites to approximately 60 re 1 where SAV dominated the O 2 -supersaturated water column. The strongest attenuation occurred between 15-17 , consistent with the resonance scattering of sub-millimetric photosynthetic air bubbles. However, measurable attenuation across a wider frequency band suggests a broader distribution of bubble sizes and additional vegetation-related mechanisms. This study highlights the potential role of SAV in attenuating mid- to high-frequency acoustic energy, which may contribute to noise mitigation in freshwater ecosystems hosting a wide diversity of aquatic 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".