Wind noise source level and Bio-Goose: Perspectives on Doug Cato’s contributions in ocean ambient noise
Bibliographic record
Abstract
Doug Cato’s research has provided insights that form the basis of our understanding of ambient noise in the ocean. This paper focuses on only two aspects of ambient noise that are strongly linked to Doug’s work. One is source level of ambient sound due to local wind at the sea surface. Estimates of wind sound source level derived from noise measurements with vertical line hydrophone arrays are shown to be consistent with the levels for noise due to wind reported in the Cato curves—up to date relationships for levels of components of ambient noise over a wide frequency band. The second aspect revisits a curious sound that was recorded in waters around Australia and New Zealand some years ago. The sounds were believed to be generated by marine animals, but the type of creature was not identified at sea or in subsequent analysis. Owing to the limited bandwidth of the recordings, the sound was accordingly dubbed as Bio-Duck in New Zealand and Bio-Goose in Australia. Further characteristics of the sound are presented, along with evidence of a probable conversation between two speakers and an example of the Lombard effect in the communications.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".