Magnetic Response of nth Rose Curve Resonator in the RF Frequency Regime
Bibliographic record
Abstract
Permeability function and magnetic loss tangent of a medium composed of artificial magnetic material inclusions can be expressed in terms of the perimeter and area of an inclusion.This expression of the inclusion's magnetic response in terms of the geometric properties simplifies and facilitates the design process of the inclusion.Such new inclusion's circuit model creates flexibility and allows to the designer to achieve a specific constraints without the use of the intensive full wave electromagnetic simulation.In this paper, we apply a generalized model of the resonant behavior of an inclusion to study the nth order rose curve resonator (n-RCR) electromagnetic response.This study is based on a numerical and analytical simulation.A detailed parametric study on the transmission characteristics and the magnetic behavior of the n-RCR based on its physical and geometrical parameter is presented.The studied geometrical parameters are the perimeter, the area and the order of the rose curve resonator.Moreover, the width and the height of the printed conductor are defined as the principle physical parameters that will be analysed and investigated.Nth Rose curve resonator is a novel curve, considered as a generic candidate for the artificial magnetic materials and provides new characteristics not found in traditional resonators.
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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 | 0.000 | 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) | 0.003 | 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".