Passive seismic for optimized geotechnical design: A case study of the Wakrah pump station
Bibliographic record
Abstract
Passive seismic interferometry is a data-driven method that reorganizes ambient seismic noise into interpretable signal. This signal can be used in a tomographic inversion to create a 3D map of shear wave velocity, a subsurface property directly related to the small-strain shear modulus needed for geotechnical design of foundations and subsurface infrastructure. Using passive seismic, we can also exceed the depth penetration of most conventional methods (for example, MASW) by providing screening down to 100 m or more, which is sufficient for the very deepest foundation and for most subsurface excavations in infrastructure development. We present a case study of the Wakrah pump station in Qatar to demonstrate that the use of passive seismic screening is an important step towards accelerated site characterization by enabling the reduction of intrusive investigations and lighter, more sustainable engineering due to optimally designed foundations and infrastructure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".