The impact of ocean sound speed variability on the uncertainty of geoacoustic parameter estimates
Why this work is in the frame
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Bibliographic record
Abstract
This paper investigates the influence of water column variability on the estimates of geoacoustic model parameters obtained from matched field inversions. The acoustic data were collected on the New Jersey continental shelf during shallow water experiments in August 2006. The oceanographic variability was evident when the data were recorded. To quantify the uncertainties of the geoacoustic parameter estimates in this environment, Bayesian matched field geoacoustic inversion was applied to multi-tonal continuous wave data. The spatially and temporally varying water column sound speed is parametrized in terms of empirical orthogonal functions and included in the inversion. Its impact on the geometric and geoacoustic parameter estimates is then analyzed by the inter-parameter correlations. Two different approaches were used to obtain information about the variation of the water sound speed. One used only the profiles collected along the experimental track during the experiment, and the other also included observations collected over a larger area. The geoacoustic estimates from both the large and small sample sets are consistent. However, due to the diversity of the oceanic sound speed, more empirical orthogonal functions are needed in the inversion when more sound speed profile samples are used.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it