Measurement and modeling of elliptical particle motion in the seabed
Bibliographic record
Abstract
As part of the SAX04 experiment conducted off the coast of Florida in the Gulf of Mexico, four vector sensors containing three-axis accelerometers and pressure sensors were buried in the seabed. These served as the receivers to measure sediment sound-speed dispersion using a variety of techniques. One technique involved the generation of spherical waves from a point source in water and transmitted into the seabed in the frequency band 800 to 3000 Hz. In this geometry, the contribution of inhomogeneous waves to the field results in elliptical—rather than longitudinal—particle motion. The orientation of the elliptical orbit varies with the source-receiver geometry, frequency, and the sediment sound speed, thereby allowing measurements of sediment sound-speed dispersion. However, the orientation of the ellipse major axis is not always aligned with the direction of wave propagation suggested by Snell’s law. Measurements were made at several angles approaching the nominal critical angle in order to address the trade-off between increased sensitivity of the measurement versus greater departure from Snell’s law. Measurements and modeling of the elliptical particle motion are compared to ensure that the sediment sound-speed estimates account for any bias created by the inhomogeneous waves. [Work partially supported by ONR.]
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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 | 0.001 |
| 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) | 0.000 | 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 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".