MATCHED FIELD TOMOGRAPHIC INVERSION TO DETERMINE RANGE DEPENDENT GEOACOUSTIC PROPERTIES
Bibliographic record
Abstract
The paper describes a new broadband tomographic matched field method for estimating the geoacoustic properties of a range-dependent shallow water environment. This method is designed for a multiple acoustic element configuration (several sources and vertical arrays deployed in an ocean region) in order to estimate the range and cross-range properties of the sediment over the region. The synthetic pressure fields (replicas) for the tomographic inversion are computed using a ray model. A linear processor operating in the frequency domain is used to quantify the match between replica and measured fields. This processor is based on coherent summations over frequencies and receiver pairs. The method is demonstrated for a geoacoustic ocean model simulating the environment of the Haro Strait experiment. The area is divided into cells in which the geoacoustic properties are range independent but can vary from one cell to another. The layer thickness can vary within a cell. Results are presented for the estimation of the compressional velocity and sediment layer thickness in the ideal case of a noise free synthetic data set.
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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) | 0.002 | 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".