Post-Processing Continuous Shear Wave Signals Taken During Cone Penetrometer Testing
Bibliographic record
Abstract
Abstract Continuous seismic velocity measurements use a special automated wave source and advanced post-processing analyses to provide fast, detailed, and reliable profiles of shear wave velocity (Vs) with depth. Conventional geophysical techniques such as crosshole tests (CHTs) and downhole tests (DHTs) in boreholes are slow because they have several required steps: (1) rotary drilling, (2) installation of casing and grouting, (3) inclinometer measurements (for CHTs), and (4) deployment of geophones for seismic readings. Direct-push technologies include the use of seismic cones and seismic dilatometers that offer DHT-type Vs data at intervals of 1 m or less without the need for drilling, casing, grouting, or separate field events. The recent development of a new portable autoseis source allows the generation of reliable and consistent shear waves either intermittently or as frequently as every 1 to 10 s. Continuous shear wave measurements can provide improved detailing of the small-strain stiffness (G0) at frequent depth intervals and fast field production times. Appreciable sensitivity errors in Vs calculations can be experienced because of the extremely small time shifts between adjacent shear wave records, as well as significant signal noise due to vibration, external sources, and refracted waves. This paper details continuous-interval seismic piezocone testing and explains how to handle signal post-processing in both the time domain and the spectral frequency domain in order to obtain a reliable in situ Vs profile.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".