Geoacoustic inversion of the New England Mud Patch using modal time-frequency dispersion
Bibliographic record
Abstract
This paper presents geoacoustic inversion of several low-frequency broadband signals recorded during the Seabed Characterization Experiment (SBCEX) that took place on the New England Mud Patch in March 2017. The considered sources are chirps emitted by a towed J15 source and underwater impulses created by MK64 explosions. These sources are low-frequency (f<250 Hz) so that the shallow water environment acts as a dispersive waveguide, and propagation is conveniently described by modal theory. The received signal is recorded on a single hydrophone placed 0.8 m off the bottom. In this context, inversion is carried out by matching modal dispersion curves in the time-frequency domain. Experimental dispersion curves are estimated using a non-linear sampling scheme called warping. Up to six modes can be estimated, and non-linear inversion results are consistent with what is known about the area.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 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".