A comparison of Electric Field sensors distortion characteristics in the Hermite-Gauss signal subspaces
Bibliographic record
Abstract
In addition to the classical time-domain distortion characteristic known as fidelity, one can evaluate sensor distortion characteristic using the transformation matrix concept in linear algebra. In this paper, electromagnetic field sensor transformation matrix is calculated based on a set of Hermite- Gauss orthonormal functions. The transformation matrices are calculated for a 5-cm Asymptotic Conical Dipole (ACD), wire monopoles of lengths 5 and 8.5 cm, and L-antennas with the same heights using the simulated voltages. The simulation is performed by solving an Electric Field Integral Equation (EFIE) on wire structures using the Method of Moments (MoM). Transformation matrices are calculated for the sensors with the same level of sensitivity as a measure of distortion. Transformation matrices are compared to each other using a numerical measure.
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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) | 0.000 | 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) | 0.000 | 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".