Bibliographic record
Abstract
Airborne noise from breaking waves is an important component of the ambient noise in coastal areas.The surf noise may mask unwanted noise arising from sources such as offshore wind turbines or naval gunfire exercises.Work is being undertaken on behalf of the Department of National Defence (DND) to determine whether naval gunfire exercises may have an impact on bird colonies, nesting areas, or other sensitive sites on land in close proximity to naval operational areas.In order to determine whether the received sound pressure level from naval gunfire is above the ambient sound level at these sites, the ambient sound level in coastal areas as a function of sea state and weather conditions needs to be understood.Underwater noise originating from breaking waves has been well-studied (e.g., [1]); however, there are fewer published papers on the corresponding airborne noise.Bolin and Abom [2] measured airborne surf noise in third-octave bands as a function of significant wave height in ten locations along the Baltic Sea coast.They proposed several mechanisms for sound generation, including impact noise, single oscillating bubbles, collective bubble oscillation, and bursting bubbles; they also proposed a semi-empirical sound generation-propagation model.This paper describes a similar experiment and compares the results to those of Bolin and Abom.
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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 | 0.003 |
| 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) | 0.003 | 0.001 |
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".