Geoacoustic inversion of broadband data in the Florida Straits
Bibliographic record
Abstract
Acoustic propagation experiments have been carried out in the Florida Straits with a multi-frequency broadband source that transmitted m-sequence pulses over a range of 10 km to a sparse-filled vertical line array. This paper presents results of matched field inversions of the acoustic field data at low frequencies to estimate geoacoustic model parameters for the experimental site. Two approaches were taken for the inversions. The first was a conventional matched field inversion using multi-frequency data centered at 200 and at 400 Hz from the vertical array. The second approach was designed to model the low frequency waveform at a single hydrophone. For the very long range experimental geometry, the waveform was modeled in terms of modes. Each inversion was cast as an optimization problem using the adaptive simplex simulated annealing algorithm. The inversions provide a comparison between approaches that take advantage of the spatial coherence in one case, and the time coherence in the received signal in the other case. Both inversions give similar results for the parameters of a simple geoacoustic bottom model, and the sensitivities and relative uncertainties of the model parameters are consistent for the two approaches. Notably, the inversions are sensitive to compressional wave attenuation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".