A phase regulated back wave propagation technique for geoacoustic inversion
Bibliographic record
Abstract
An inversion method based on the concept of back wave propagation (BWP) is described in this paper for estimation of geoacoustic parameters from acoustic field data. A phase-regulation technique is introduced to increase the sensitivity of the method for geoacoustic model parameters having low sensitivity. The case of data consisting of signal plus additive noise is also addressed. It is shown theoretically that the sensitivity can be increased by a factor alpha using the phase regulation procedure, and that the spatial resolution of signal energy that is concentrated by BWP at the known source position is increased when a increases. This result suggests an effective criterion for use in the inversion, based on the spatial distribution of signal energy around the true source location. The basis for the criterion is the spatial variance of the back-propagated pressure field in a window around the known source location. A multistep search process is proposed to avoid using a complicated multidimensional search process. Inversion results from both simulations and experimental data are given. The real data were taken from the Pacific Shelf experiment carried out in shallow water off the West Coast of Vancouver Island in the Northeast Pacific Ocean.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".