Geoacoustic inversion of M-sequence data from experiments in the South Florida Straits
Bibliographic record
Abstract
Matched field inversion is applied to low frequency data from experiments in the South Florida Straits to estimate a sediment velocity profile. The acoustic data consist of signal envelopes derived from M-sequences that were transmitted to a vertical hydrophone array over a range of 10 km. The sound speed profile supported a strong waveguide in the deeper parts of the water column. Signal propagation for a source in the waveguide was dominated by waveguide refracted paths, and surface-reflected bottom-reflected paths that interacted eight to ten times with the bottom. The very long range, shallow water geometry presents a significant challenge for an inversion based on matched field processing. However, examination of the spatial coherence of the received signal indicated useful spatial phase information for spectral components with high signal-to-noise ratios. A Gibbs sampling approach was used to test two different geoacoustic models for the site: (a) a constant gradient sediment and (b) a constant velocity sediment over a half space. The inversion showed a preference for slower speeds of around 1550 m/s at the sea floor, increasing to higher values up to 1700 m/s within about 100 m deeper. These values are consistent with ground truth at the site.
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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) | 0.000 | 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 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".