Geoacoustic inversion of modal dispersion on the New England Mud Patch. I: Experimental quantification of information content in higher-order modes
Bibliographic record
Abstract
This paper presents the results from a geoacoustic inversion study performed using a combustive sound source signal recorded on a vertical line array during the 2017 Seabed Characterization Experiment (SBCEX17). A single receiver modal estimation method (source deconvolution and warping) is recursively applied along the array channels to estimate modal time-frequency dispersion, resulting in modal dispersion data for 18 modes between modes 1 and 21. These data are then used as an input for trans-dimensional Bayesian geoacoustic inversion. The paper compares inversion results obtained with subsets of modes (1 to 7 and 1 to 15) to those obtained with the whole set (modes 1 to 21) to explore the data information content associated with high-order modes. The study shows that high-order modes enable the resolution of fine details in the seabed sound-speed profile, such as a small sound speed increase over the first 8 m of the seabed (i.e., within the upper portion of the so-called “mud layer,” an important feature of the experiment area). [Work supported by the Office of Naval Research.]
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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) | 0.001 | 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".