IEEE Transactions on Antennas and Propagation Announces a Special Issue on Theory and Applications of Characteristic Modes
Bibliographic record
Abstract
The Theory of Characteristic Modes (TCM) had its humble beginnings in the early 1970's. The beauty of TCM lies in its ability to fully characterize the radiation and scattering properties of an arbitrary object based only on the object's geometry and material properties. This ability provides valuable insights into an antenna's behavior independent of the feeding arrangement as well as providing information about how desirable radiation modes can be excited. This feature has led to its use to design integrated antennas in the High Frequency (HF) band for land vehicles, ships and aircraft. However, TCM had largely remained a specialist field until it was rediscovered for aiding the design of mobile handset antennas about a decade ago. In particular, TCM provides a powerful tool to understand and exploit excitation of the terminal chassis to enhance antenna performance. Another powerful feature of TCM is that multiple characteristic modes at a given frequency facilitate orthogonal radiation patterns, which provide effective Multiple-Input Multiple-Output (MIMO) antennas.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.031 | 0.022 |
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".