<i>In situ</i> sediment dispersion estimates in the presence of discrete layers and gradients
Bibliographic record
Abstract
One of the difficulties in validating sediment models has been the lack of reliable low frequency dispersion measurements. A reflection method is presented that yields in situ dispersion without sediment disturbance over a broad range of frequencies and can explicitly disentangle frequency-dependent effects of vertical structure, e.g., layers and gradients. Measurements on the outer shelf from 300 to 3000 Hz show that dispersion is a strong function of depth in the sediment column. The depth and frequency-dependent results generally agree well with independent measurements on core data. Cohesive sediments in the upper few meters exhibit a nearly frequency-independent sound speed and a nearly linear frequency dependence of attenuation. In the lower part of the sediment column the sediments are more granular: the lowest layer exhibits an attenuation with a peak frequency at 1100 Hz, where its dependence below and above trends to f(2) and f(1/2), respectively. While Biot theory predicts this dependence, its underlying physical explanation, fluid flow through interstitial pores, does not seem plausible for this sediment due to the unreasonable permeability value required. Viscous grain shearing theory also predicts this dependence, but it is not known whether the parameter values are reasonable.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".