Bibliographic record
Abstract
Anthropogenic underwater noise is an increasing environmental concern. Accurate predictions of sound levels from anthropogenic sources are required to estimate the impact on marine life exposed to it. JASCO Applied Sciences has been developing software modeling tools for underwater noise exposure estimation for more than 30 years. Elements of the modelling process include estimation of source level, spectrum, and radiation pattern; environmental characteristics of the underwater sound medium and the geoacoustics of the seabed; calculating the acoustic propagation loss; estimating the received levels, both in terms of rms SPL and Sound Exposure Level (SEL); evaluating species-specific impact weighting; and compiling results into comprehensible summaries. These tools have been developed for accuracy in prediction and efficiency in computation, and have been used in work for a wide range of international clients, both commercial and governmental. This paper presents an overview of the anthropogenic underwater noise and exposure modelling work being done by JASCO.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 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 teacher head, 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".