Passive Acoustic Glider for Seabed Characterization at the New England Mud Patch
Bibliographic record
Abstract
Acoustic payload-equipped underwater gliders are proving to have great potential for maritime intelligence, surveillance, and reconnaissance missions, as well as oceanic environment characterization. This article demonstrates their capabilities for seabed characterization using broadband signals received on a hydrophone-equipped Teledyne Webb Research Slocum glider during the 2017 Seabed Characterization Experiment (SBCEX) conducted on the New England Mud Patch. In the experiment, a source ship maintained a fixed position while combustive sound-source signals were emitted at about 2 min intervals. The glider was programmed to follow a sawtooth-like track through the water column approximately 8 km from the source in an area where the water was ∼72 m deep. Two transmissions were received by the glider at depths separated by about 15 m. Trans-dimensional Bayesian geoacoustic inversion was applied to modal-dispersion data extracted from the received signals via a time-warping technique to study the consistency of the inversion results for signals received at different depths, and the advantages of including signal receptions at different depths in simultaneous inversion. The inferred geoacoustic properties are in good agreement with independent core measurements collected during a geophysical survey, and with other inversion results using data collected by dedicated bottom-moored receivers in the vicinity.
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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 | 0.000 | 0.000 |
| 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 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".