Measurement of Bulk Electrical Properties Using GPR with a Variable Reflector
Bibliographic record
Abstract
ABSTRACT Bulk electrical properties of media are important inherently for ground penetrating radar (GPR) applications and for providing a means to determine indirectly other physical properties such as moisture content. We have developed a reflector whose reflectivity can be controlled electronically. This variable reflector controlled by a GPR provides an effective method to measure bulk electrical properties of media. For sample measurements, the GPR is placed on one side of a sample and the variable reflector on the opposite side. GPR trace data are then acquired with the reflector in an on-state and in the off-state. By differencing these measurements, we improve the ability to detect the specific reflection event from the variable reflector. This process removes both the direct wave and clutter from the trace data, improving the quality of the refection event and our ability to accurately pick its arrival time and amplitude. We describe the variable reflector, a prototype instrument based on the reflector and numerical modeling performed to understand its response. We also show the results of testing applications to the measurement of wood chip moisture content and monitoring of the electrical properties of concrete during the curing process.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".