Matched field inversion with a moving source in a shallow-water environment
Bibliographic record
Abstract
Geoacoustic inversion based on matched field processing (MFP) is examined for shallow-water, low-frequency environments. Specific interest lies with resolving geoacoustic parameters from cw tones projected from a moving source. Data obtained using vertical line arrays (VLA) are available from both the 1996 Haro Strait PRIMER Experiment (HSX) and the Santa Barbara Channel Experiment (SBCX) of 1998. The environmental complexity associated with these experiments, namely, strong range-dependent bathymetry and current flow, is typical to littoral environments in general and must be appropriately addressed. Parabolic equation modeling is used as it provides range-dependent results. The VLA receiver configuration is described as a catenary which is typical of bottom-anchored arrays drifting in uniform current flow. Both SBCX and HSX are useful for benchmarking geoacoustic inversion techniques since results from other techniques are available. Estimation of bottom properties is discussed as a function of propagation range, ship track with respect to receiver position, and general bathymetric features. Results for both tangential and radial tracks are presented. [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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".