Estimating the speed of poroelastic interface waves using ambient noise
Bibliographic record
Abstract
Pairs of hydrophones were buried at mid-tide height in a 1:10 sloped mixed gravel and coarse sand beach and used to make ambient noise recordings over a period of three weeks in Advocate Harbour, Nova Scotia, in the Bay of Fundy. The pairs were arranged in vertical and horizontal configurations and recorded pressure time series, power spectral density, and vertical and horizontal coherence measurements of the noise field in the seabed. A nearby suite of oceanographic instruments measured the water level, ocean wave properties, bed dynamics and weather during the experiment. The measured noise between 1 Hz and 1 kHz was dominated by poroelastic interface waves generated by plunging surf on the beach face. The speed of the compressional component of the interface wave was estimated by cross-correlating the noise recorded on the across-shore oriented pair of sensors while the unconsolidated sediment was water-saturated as well as drained. Additionally, the increasing and decreasing overburden pressure due to the rising and falling 10-m tide was found to drive a respective increase and decrease in the poroelastic interface wave speed. A buried acoustic source was used to directly measure the compressional wave speed in the seabed on the across-shore array.
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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 | 0.000 |
| 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".