Seabed Analysis on the New England shelf break using ambient sound data and trans-dimensional geoacoustic inversion
Bibliographic record
Abstract
The New England Shelf Break Acoustics (NESBA) Signals and Noise experiment was conducted in April-May 2021. Ambient sound data were collected over several days in the mud-patch area as well as in deeper water closer to the shelf break. A 16-hydrophone vertical array was used to measure the natural sound of breaking waves on the sea-surface. Using beamforming in the 500–700 Hz band, these data were used to obtain an estimate of the bottom reflection coefficient as well as the seabed layering. The reflection coefficient data were subsequently used with trans-dimensional inversion techniques to produce a geoacoustic model for the seabed (e.g., sound speed, density, and layering). Results show the ambient sound data can be used to produce well resolved geo-acoustic parameters, especially in the upper part of the seabed (e.g., <10 m). These results are compared between several locations on the New England Shelf Break area and are also compared with other published results using different estimation techniques. In addition, some of the issues related to the impacts of data errors and preferred measurement geometries will also be presented. [Work supported by the Office of Naval Research.]
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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".