Identification and Isolation of Multiple Modes in Rayleigh Waves Testing Methods
Bibliographic record
Abstract
The spectral-analyses-of-surface-waves (SASW), developed in the early eighties, has constituted an important step, in the use of surface waves for definition of shear wave velocity profiles without intrusion. The SASW testing procedure was designed to minimize the contribution of higher Rayleigh modes and thus assumes that the average dispersion curve is representative of the fundamental Rayleigh mode. A number of numerical studies have however demonstrated that this basic assumption is valid only when the shear wave velocity varies regularly with depth. This study demonstrates, based in numerical simulations and an experimental case, that the multi-Rayleigh mode problem can occur in various situations even if the shear wave velocity increases regularly with depth. Techniques are proposed in order to identify and separate the energy of higher modes. The applicability of those techniques is demonstrated with simulated and experimental cases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".