THE MICROVIBE, A NEW MULTI-COMPONENT PORTABLE SEISMIC VIBRATOR
Bibliographic record
Abstract
From our own observations and those reported in the literature, relatively large seismic vibrators mounted on trucks are limited in their ability to generate energy above 225 Hz. To improve high frequency energy transfer into the ground, we have developed a 400 Watt, two-component 70 kg vibrator that we have named the “Microvibe.” Mounted with 6 off-the-shelf tactile transducers in both the vertical (V) and horizontal transverse (H2) directions, this vibrator can provide various types of linear and non-linear sweeps from 20 Hz up to 800 Hz with a 3900 N theoretical peak force for each component. This is approximately 15% of the energy provided by an IVI buggy-mounted Minvib I. In order to help compensate for the reduced energy levels, we increase the time length of the sweep. Our experiments have shown that shear wave energy is minimal above 300 Hz. In comparison, it is common to obtain P-wave reflections at 800 Hz over every type of soil that has been tested so far. The concept of operating with two components mounted on a single device is innovative, providing new insights into near surface shear wave anisotropy and birefringence. We compare data obtained with both the Minivib I and our Microvibe sources. Besides improved resolution, a significant advantage of using the Microvibe portable source is the considerable reduction of the acquisition costs for near surface, high resolution seismic reflection data.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".