A study of the connection between tidal velocities, soliton packets and acoustic signal losses
Bibliographic record
Abstract
Coupled ocean model and acoustic model simulations of soliton packets in the Yellow Sea have indicated that the environmental conditions necessary for anomalous signal losses can occur several times in a 24 h period. These conditions and the subsequent signal losses were observed in simulations made over an 80 h space–time evolution of soliton packets that were generated by a 0.7 m/s tidal velocity [Chin-Bing et al., J. Acoust. Soc. Am. 111, 2459 (2002)]. This particular tidal velocity was used to initiate the Lamb soliton model because the soliton packets that were generated compared favorably with SAR measurements of soliton packets in the Yellow Sea. The tidal velocities in this region can range from 0.3 m/s to 1.2 m/s. In this work we extend our simulations and analyses to include soliton packets generated by other tidal velocities in the 0.3–1.2 m/s band. Anomalous signal losses are again observed. Examples will be shown that illustrate the connections between the tidal velocities, the soliton packets that are generated by these tidal velocities, and the signal losses that can occur when acoustic signals are propagated through these soliton packets. [Work supported by ONR/NRL and by a High Performance Computing DoD grant.]
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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 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".