Seabed characterization using ambient sound for a range-dependent track in the New England Mud Patch
Bibliographic record
Abstract
Wind-generated, ocean ambient sound data were used to characterize seabed properties along a track in the New England Mud Patch. A 15-m vertical array, consisting of 16 hydrophones, collected ambient sound data across the 50-5000 Hz frequency band. The array drifted for 1 h, covering a 1.7 km track. Seabed characterization was performed using beamforming techniques, which limited the analysis to the 400-700 Hz band. Passive fathometer processing was applied to estimate the water-seabed interface and sub-bottom layering. Additionally, the data were used to estimate the power reflection coefficient, which was then used as input for a trans-dimensional geoacoustic inversion. The results showed the track had slight range dependence, which was evident in the layering structure. The estimated seabed properties-sound speed, density, and attenuation-were consistent along the track but also showed slight range-dependent variability.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".