Trans-dimensional inversion for sediment attenuation using modal dispersion data collected by an underwater glider
Bibliographic record
Abstract
This paper inverts modal-dispersion data collected by an underwater glider to estimate a layered seabed geoacoustic model including sediment attenuation as well as sound speed and density. The data considered here were collected during the 2017 Seabed Characterization Experiment (SBCEX17) conducted on the New England Mud Patch. The distance between the (combustive) sound source and the hydrophone-equipped (Teledyne Webb Research Slocum) glider was approximately 8 km. The frequency range considered was from 20 to 392 Hz, and 6 modes were resolved from the data using warping. Previous work has demonstrated that the positions of dispersive acoustic modes in the time-frequency plane provide information to estimate seabed sound-speed and density profiles. Including the relative energy distribution in the time-frequency plane (normalized modal amplitudes and/or amplitude ratios between modes) provides additional information to also estimate sediment attenuation, which is carried out here using a trans-dimensional Bayesian inversion. In addition, uncertainties of the seabed sound speed and density with/without modal energy information are compared. [Work supported by ONR.]
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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 | 0.001 | 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".