RWG MoM‐via‐locally corrected Nyström method in near‐field to far‐field transformation using very‐near‐field measurement
Bibliographic record
Abstract
Locally corrected Nyström (LCN) method is used to solve electric field integral equations (EFIE) of the equivalent current method in the planar very‐near‐field measurement of antennas and RF circuits. The exact relationship between the Rao–Wilton–Glisson (RWG) method of moments and first‐order and zero‐order LCN is established for both magnetic and electric currents to ensure normal current continuity between adjacent triangular patches. The proposed method is a point‐based RWG discretisation of EFIE and causes a noticeable decrease in the degree of freedom. It consequently eliminates spurious charges and significantly lowers the condition number of the impedance matrix. Moreover, it is more efficient to be accelerated by fast algorithms such as multi‐level fast multipole method. In what follows, the detailed explanation of the proposed method, along with the examples of current reconstruction and antenna far‐field calculation, is presented.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".