Seabed geoacoustic inversion using a hydrophone equipped underwater glider
Bibliographic record
Abstract
The reflection coefficient at the sea floor as a function of grazing angle contains seabed geoacoustic properties that are crucial for predicting sound propagation accurately. NATO—STO—CMRE has developed a new technique for remote sensing the seabed reflection coefficient using underwater gliders equipped with passive acoustic payloads. This technique was applied during ONR sponsored Seabed Characterization Experiment conducted on the New England Mud Patch, USA, in March 2017. The reflected field was measured between grazing angles of 3.5 to 260, and frequency band of 2–20 kHz by an omni-directional hydrophone equipped Slocum glider, with the assistance of a broadband acoustic source. The data were analyzed both in time and frequency domains to obtain the reflection coefficient as a function of grazing angle at different frequencies. Ray tracing was also employed to fine tune the grazing angle information. Finally, Bayesian geoacoustic inversion of the reflection data at different frequencies was carried out. As a preliminary inversion attempt, the reflection data were modeled assuming a plane wave reflection coefficient. [Work funded by NATO-Allied Command Transformation, Office of Naval Research and Office of Naval Research—Global.]
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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".