CHARACTERIZING AND MODELLING OCEAN AMBIENT NOISE USING INFRASOUND NETWORK AND MIDDLE ATMOSPHERIC MODELS
Bibliographic record
Abstract
Infrasound is one of the technologies of the International Monitoring System (IMS) supporting the verification regime of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). In the frequency band of interest to detect atmospheric explosions, ambient noise may affect detection and particularly ocean noise referred to as microbaroms. Ocean wave interactions generate acoustic noise almost continuously which can obscure signals of interest in their frequency range. The detectability of such noise strongly depends on atmospheric conditions along the propagation paths. Using ocean wave action model developed by IFREMER and considering the effects of general middle-atmospheric products delivered by ECMWF in long-range propagation, microbarom amplitudes and direction of arrivals derived from various propagation models are compared with the observations. With this study, it is expected to enhance the characterization of the ocean-atmosphere coupling. In return, a better knowledge of microbarom sources would allow to better characterize explosive atmospheric events hidden in the ambient noise.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".