Review of Geoacoustic Inversion in Underwater Acoustics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper reviews the progress in geoacoustic inversion over the past several decades. The review is separated into two parts. The first part reviews developments in model-based inversion methods that have led to present day usage of Bayesian inference. Theoretical foundations for the inversion methods are outlined, and limitations of model-based approaches are discussed. Examples are briefly described of applications of model-based inversion with different types of experimental data. The second part reviews recent developments in model-free inversion methods, focusing on discussion of distortion of estimated geoacoustic model parameters caused by model mismatch. It is shown that distortions in estimated model parameters lead to errors in interpreting characteristics of dispersion in the ocean waveguide, in particular the frequency dependence of sound attenuation in marine sediment. This review concludes with perspectives on new directions in research that promise improvement in inversion performance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it