Surface‐Volume–Surface Electric Field Integral Equation
Bibliographic record
Abstract
This chapter helps the reader to understand the system of coupled volume integral equation, Mixed-Potential-Integral-Equation (MPIE), and Surface-Volume-Surface-electric field integral equation (SVS-EFIE) formulated for composite metal–dielectric objects embedded in layered media and featuring both piece-wise homogeneous regions, inhomogeneous regions, and metal regions. It derives elements for impedance matrix resulting from Method of Moments (MoM) discretization of SVS-EFIE. Coupled system of SVS-EFIE, MPIE, and volume integral equation enables solution of the scattering and radiation problems involving realistic composite metal–dielectric models with piece-wise and inhomogeneous dielectric regions embedded in a multilayered media. MoM discretization of such models involves volumetric meshes (e.g. tetrahedral ones) representing dielectric regions and surface meshes (e.g. triangle ones) representing the metal regions and surfaces bounding the piece-wise homogeneous dielectric regions. Michalski-Zheng's theory allows reduction of the singularity in the scalar potential part of the electric field Green's function to 1/R strength through use of divergence and gradient theorems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".