Relating GPR system parameters to regulatory emissions limits
Bibliographic record
Abstract
Abstract Ground penetrating radar (GPR) is regulated regarding emission limits for ultra‐wideband in a number of jurisdictions. The definitions of these regulations employ concepts and terminology that are more suited to traditional narrow band radio transmitters. Further, the emissions limits were based on limited quantitative factual information and have resulted in stringent limitations on GPR technology advancement. Factual theoretical and experimental information on the emissions from actual GPR devices is not generally available, and the relationship with regulatory requirements is poorly understood by users. This information gap must be filled if a compelling argument for less stringent emissions levels is to be mounted in the future. Moreover, the current regulations have the potential to trigger further review of emission limits in the future which could be detrimental to the use of GPR. In this paper, we present the basic steps entailed in translating impulse time‐domain GPR instrument behaviour into ‘regulatory’ parameters. To achieve this, we also employ three‐dimensional finite‐difference time‐domain numerical modelling to simulate the transient electromagnetic field variation around dipole antennas placed on the surface of a half‐space or at a height over it to illustrate the dependency on sensor height and ground permittivity. The ultimate goal is to establish the foundation for more sensible rule making, if and when, the regulatory standards come under scrutiny for revision and further user understanding.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".