Tool for analysis of multichannel analysis of surface waves (MASW) field data and evaluation of shear wave velocity profiles of soils
Bibliographic record
Abstract
Multichannel analysis of surface waves (MASW) is a fast, low-cost, and environmentally friendly technique to estimate shear wave velocity profiles of soil sites. This paper introduces a new open-source software, MASWaves, for processing and analysing multichannel surface wave records using the MASW method. The software consists of two main parts: a dispersion analysis tool (MASWaves Dispersion) and an inversion analysis tool (MASWaves Inversion). The performance of the dispersion analysis tool is validated by comparison with results obtained by the Geopsy software package. Verification of the inversion analysis tool is carried out by comparison with results obtained by the software WinSASW and theoretical dispersion curves presented in the literature. Results of MASW field tests conducted at three sites in south Iceland are presented to demonstrate the performance and robustness of the new software. The soils at the three test sites ranged from loose sand to cemented silty sand. In addition, at one site, the results of existing spectral analysis of surface waves (SASW) measurements were compared with the results obtained by MASWaves.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".