Cross-correlated Tensor Surface Impedance Characterization of Orthogonally Discrete IMU & CMU for Impedance Modulated Metasurface
Bibliographic record
Abstract
In this article, a detailed characterization of Tensor Surface Impedance Matrix (TSIM) for orthogonally discrete inductive and capacitive meta unit-cell has been performed. Four orthogonally distributed digitally coded (i.e ${\bf 0 0},{\bf 0 1},{\bf 1 0},11)$ states have been assigned for both orthogonally discretized inductive and capacitive meta unit-cell. Tensor Surface Impedance Matrix (TSIM) is implemented for each unit cell to characterize the isotropic, non-homogeneous nature of $\overline{\overline{Z_{\text{surf}}}}$. From dispersion relation, the variation of phase velocity has been characterized for both Inductive Meta unit-cell (IMU) as well as Capacitive Meta unit-cell (CMU). Further, Cross Correlation between similar coded IMU and CMU has been performed to extract the linear dependency of those complementary structures. Also, the Cross correlation between the proposed orthogonally discrete unit-cells have been performed to extract the equivalent impedance coupling factor $(\ddot{}{Z}_{c})$. Effective $\overline{\overline{Z_{\text{surf}}}}$ vs direction of surface wave propagation $(\theta_{k})$ is characterized for each orthogonally discrete unit cell for both proposed IMU and CMU.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".