Estimating geoacoustic properties of marine sediments by matched field inversion using ship noise as a sound source
Bibliographic record
Abstract
The first stage of a seafloor observatory to monitor marine gas hydrates will be deployed in the Gulf of Mexico in the fall of 2005. One component of the monitoring station is a vertical line hydrophone array moored on the seafloor. This paper reports research to investigate using matched field inversion of sound generated by passing ships to detect changes in the geoacoustic parameters of the seabed that may indicate the occurrence of a gas hydrate dissociation event. First, synthetic multifrequency data were used to investigate the performance of the inversion method for estimating sediment sound speeds near the seafloor. The synthetic data were generated using the parabolic equation method for a geoacoustic environment that simulated the seabed at the site in Mississippi Canyon. The geoacoustic model consisted of a multilayered structure with relatively slow sound speeds to significant depths below the seafloor. The inversion based on normal mode replica fields indicated that performance strongly depends on using a realistic parametrization of the geoacoustic model. Experimental ship noise data were recorded along radial tracks in a preliminary deployment of the vertical array. Results are reported for estimating a geoacoustic model from the noise data.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".