Understanding the use of ground-penetrating radar for assessing clandestine tunnel detection
Why this work is in the frame
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Bibliographic record
Abstract
Abstract We provide a coherent approach for developing an understanding of how and where ground-penetrating radar (GPR) can be deployed for tunnel detection. While tunnels in general are of interest, the more specific focus is tunnels that are hand dug or created with a minimal amount of equipment and resources for clandestine purposes. Determining whether GPR can be used for tunnel detection is impossible without an in-depth knowledge of the operational environment and constraints. To effectively address the question, we define the general characteristics of clandestine tunnels, discuss how to estimate the responses amplitude, define the dominant noise types associated with GPR data, and point out how those factors are affected by the GPR system. The key aspects are illustrated using a controlled field case study.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 it