Measurements of attenuation of sound in marine sediments at low frequencies.
Bibliographic record
Abstract
This paper describes an experimental technique for measuring the attenuation of sound in marine sediments at low frequencies. The method makes use of the signals from sub-bottom reflectors that are received on a vertical hydrophone array at close ranges in shallow water environments. The signal path geometry is determined from an inversion of the travel time differences of the sea bottom and sub-bottom reflected paths to estimate the sediment sound speed and the depth of the sub-bottom reflector. The method is applied to data from experiments carried out at a site on the New Jersey continental shelf in the Shallow Water 06 experiment. The sediment type and the structure of the sediment column were ground truthed by independent measurements at the site. The chirp signal was transmitted in two frequency bands, from 100–900 and 1500–4500 Hz, and the data were match filtered to obtain the multipath signals at the array. A prominent signal from a sub-bottom interface known as the R-reflector was resolved in the data for each frequency band. Results are presented for the average attenuation over the depth to the reflector. [Work supported by ONR Ocean Acoustics.]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".