Analysis of the effect of water column sound speed variation on geoacoustic inversion
Bibliographic record
Abstract
Bayesian matched field inversion has been applied on multi-tonal data sets acquired on the New Jersey continental shelf in the SW06 experiment in August, 2006. Since the data sets were collected in a range-dependent environment due to water column sound speed variation, sound speed profile (SSP) was decomposed in terms of empirical orthogonal functions and also inverted in the inversion. This presentation examines the sensitivity of the geoacoustic and geometrical parameters to the shape and the gradient of the sound speed in the thermocline by the interparameter correlation from the inversion. The effects of the SSP on the geoacoustic inversion and source localization are studied through the inversions of measured data at different ranges with/without prior information about geometric parameters in the inversion. Further investigations on the variation of SSP to the sediment sound speed, density, and attenuation at different ranges are carried out by simulations. It is found that the geometric parameters are more sensitive to the SSP than are the geoacoustic parameters in this shallow water environment. [Work supported by ONR.]
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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 | 0.002 | 0.014 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".