Geotechnical site characterization using multichannel analysis of surface waves: A case study of an area prone to quick‐clay landslides in southwest Sweden
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Quick‐clay landslides are important geohazards in Sweden, Norway and Canada. While they have been studied using various geotechnical and geophysical methods, only a handful of seismic surveys have been reported for their studies. Here, we reprocess active‐source seismic data from a quick‐clay landslide site in southwest Sweden to complement earlier studies of reflection imaging and first‐break traveltime tomography with surface‐wave dispersion analysis. Results suggest extremely low shear‐wave velocities, even as low as 60–100 m/s. From a geotechnical perspective, this implies that the region classifies as a high‐risk zone for landslides and construction purposes. High or anomalous values of Poisson's ratio (or similarly P‐ and S‐wave velocity ratio) depict a zone within the normally consolidated sediments that likely represents a coarse‐grained layer, thus confirming earlier results from a number of boreholes drilled in the study area. Overall, the results presented further support to the previous hypothesis that the coarse‐grained layer plays a major role in the formation and creation of quick‐clay landslides in the study area. Additionally, an attempt to model the distribution of potential quick clays along one of the seismic profiles is performed through a combination of the modelled geophysical properties and soil textures. This study illustrates the potential of seismic methods, and how the integration of multiple geophysical properties and different data handling strategies can help to accurately characterize regions susceptible to quick‐clay landslides.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| 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 it