High-resolution bottom-loss estimation using the ambient-noise vertical coherence function
Bibliographic record
Abstract
The seabed reflection loss (shortly "bottom loss") is an important quantity for predicting transmission loss in the ocean. A recent passive technique for estimating the bottom loss as a function of frequency and grazing angle exploits marine ambient noise (originating at the surface from breaking waves, wind, and rain) as an acoustic source. Conventional beamforming of the noise field at a vertical line array of hydrophones is a fundamental step in this technique, and the beamformer resolution in grazing angle affects the quality of the estimated bottom loss. Implementation of this technique with short arrays can be hindered by their inherently poor angular resolution. This paper presents a derivation of the bottom reflection coefficient from the ambient-noise spatial coherence function, and a technique based on this derivation for obtaining higher angular resolution bottom-loss estimates. The technique, which exploits the (approximate) spatial stationarity of the ambient-noise spatial coherence function, is demonstrated on both simulated and experimental data.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".