An Analytical Framework for Modeling Inhomogeneities in Open-Ended Coaxial Probe Measurements
Bibliographic record
Abstract
Open-ended coaxial probes (OECP) are commonly used for dielectric characterization, across the RF/Microwave frequency range. A significant challenge in using this measurement technique is to measure properties of inhomogeneous materials, due to the complexity of modeling the fields in the inhomogeneous sample. In this letter we present a theoretical model and an experimental verification for the extraction of the physical parameters of a small scatterer from open-ended coaxial probe reflection measurements. Using an analytical framework, we show that the depth and radius of a conductive scatterer can be extracted from reflection data obtained using two different probes. A 3D printed inhomogeneous sample was produced by embedding a conductive scatterer within a homogeneous dielectric sample. With average relative errors of 13%−20%, the results show that two scatterer parameters (radius and depth) can be accurately estimated relying solely on the approximate, dipolar, analytical model.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".