EFFECT OF INPUT-SOURCE FREQUENCY CONTENT ON RESULTS FROM SEISMIC TECHNIQUES FOR THE VS PROFILE DEFINITION IN SPATIALLY VARIABLE SOILS
Bibliographic record
Abstract
All around the world, foundation and construction codes consider the shear wave velocity (VS) profile as a good indicator of soil stiffness. The definition of a VS profile is a very common practice for site classification and soil characterization in geotechnical engineering. In order to obtain the VS profile there are typically two approaches: direct exploration (e.g. Seismic Cone Penetration Test ‘SCPT') and indirect exploration (e.g. seismic refraction ‘SR' and multichannel analysis of surface waves ‘MASW' techniques). Both, direct and indirect techniques require the use of an energy source to generate the waves necessary to characterize the VS soil profile; for near surface (depth less than 30m) usually an impact force is used as input source. The shear wave velocity (Vs) is equal to the product of wave length (λ) and wave frequency (f). On one side, wave length represents the limitation in terms of vertical resolution for indirect techniques; the shorter the wave length, the better the vertical resolution (thinner layers can be detected). On the other side, frequency content for the input source is not very well studied and its effect on vertical resolution for the Vs profile is not very well understood. As the Vs depends only on the soils variability, there is no way to modify it in the tests; so, what is modifiable in during the test is the frequency content in the input source and as a collateral effect, the wave length.
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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 | 0.007 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".