A Complex Permittivity Extraction Method Based on Anomalous Dispersion
Bibliographic record
Abstract
A novel method to extract dielectric material parameters from the anomalous phase response is theoretically investigated and experimentally verified. A microstrip resonance circuit that operates in the anomalous dispersion spectrum is constructed by employing the material sample as the substrate. This topology results in a strongly dispersive transmission phase having a slope opposite to the case in normal dispersion. This unique phase reversal property facilitates the detection of the resonance frequency with higher accuracy. Furthermore, since the transmission phase and magnitude in the anomalous dispersive region are related through Kramers-Kronig-like equations, one phase measurement is sufficient to completely characterize a dielectric material. Five known dielectric samples are characterized and the extracted parameters are compared with the known parameters. The extracted dielectric constants are found to be within a 10% error range. The extracted resonant parameters are utilized in reconstructing the magnitude and phase spectra in off-resonance regions. The reconstructed and measured curves bear close resemblance.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".