Geoacoustic inversion of broadband data by matched beam processing
Bibliographic record
Abstract
This paper describes results of geoacoustic inversion using broadband signals from an experiment carried out at a site near the South Florida Ocean Measurement Centre in the Florida Straits. M-sequence coded pulse trains at different center carrier frequencies from 100to3200Hz were recorded at a vertical line array at a distance around 10km. Geoacoustic inversion was carried out to determine the feasibility of inverting the environmental parameters from this long-range propagation experiment. The received signal at lower frequencies below 400Hz consisted of a dominant water column signal and a secondary arrival delayed by 0.4s. The secondary signal was spatially filtered by beamforming the array data, and the beam data were inverted by matched beam processing in the time domain, combined with an adaptive simplex simulated annealing algorithm. The estimated values of compressional wave speed and density were in good agreement with ground truth values from sediment cores. The inverted shear wave speed appears to be a sensitive parameter and consistent with compressional wave speed. As a cross check, range and water depth were also included as inversion parameters, and the inversion results were close to the known values within small uncertainties.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".