Bibliographic record
Abstract
This paper considers matched-field ocean acoustic source localization based on acoustic field measurements at an array of sensors which are not synchronized in time or at an array which is comprised of non-synchronized combinations of synchronized sub-arrays. Standard matched-field methods are based on acoustic-field measurements at a time-synchronized array to allow coherent processing over space (the array aperture). For non-synchronized systems, frequency-coherent/space-incoherent processing can be applied if the complex source spectrum (amplitude and phase) is known, but this is rarely the case in practical applications. However, time- and frequency-coherent processing are not the only possibilities. Maximum-likelihood methods can be applied to derive optimal matched-field processors for any state of source/receiver information. Using this method, optimal processors can be developed for broadband matched-field localization with any combination of synchronized and/or non-synchronized components based on the fact that the source amplitude spectrum is the same (although unknown) for all receivers (the phase spectrum is both unknown and variable for non-synchronized components). Bayesian inversion methods are employed to quantify the source-localization information content for various array scenarios.
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How this classification was reachedexpand
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".