Modelling the coastal, ambient, marine noise field in space, time and frequency
Bibliographic record
Abstract
The objective of this work is to model the natural ambient noise level in coastal regions based on local environmental forcing and propagation conditions. 546 continuous hours of noise were recorded between April 15 and May 7, 2018 in Sooke Inlet, British Columbia, a coastal, shallow-water region with complex bathymetry and diverse surface traffic. Optimal 1-hour lagged correlation between raw wind speed and hourly minimum sound pressure level (dB re 1 μPa/Hz) is computed as a function of frequency. Low frequencies (10–500 Hz) are characterized by poor correlation due to flow noise and near continuous shipping and small vessel traffic. Mid-frequencies (0.5–10 kHz) show increasing correlation with the shift from ship to wind dominated forcing. High frequencies (10 kHz +) show good correlation with wind. The empirically derived relationship between noise and wind speed is used to validate a predictive ambient noise model, driven by local weather and oceanographic conditions, an acoustic transmission loss model, and a wind to wave energy model. The noise model’s sensitivity to temporal and spatial resolution of environmental and forcing data, and knowledge of bathymetry and bottom type will be quantified with the objective of model portability to other coastal regions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".