Array element localization using ship noise
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 describes a method of estimating hydrophone positions in a receiver array using the noise from a passing ship. Relative arrival times of the ship-noise signal between pairs of hydrophones are obtained from several time windows of data (corresponding to different ship locations) by cross-correlating the band-pass filtered time series. The relative arrival times are used as data in an array element localization inversion to estimate both the hydrophone and ship locations based on iterated linearization of the acoustic ray equations. The inversion applies the method of regularization to include prior information such as approximate location estimates and uncertainties for the source and receivers and the expectation that the array shape and or source tracks are smooth functions of position. Linearized and nonlinear (Monte Carlo) estimates of the position errors are in good agreement and indicate a high degree of confidence in the receiver positions (relative uncertainties of approximately 0.2 m in the horizontal and 0.05-0.1 m in the vertical). The ability to improve upon the initial source position estimates depends on the geometry of the problem, as investigated with simulations.
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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 | 0.001 | 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 | 0.001 | 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 it