Backscattering of Plane Waves from Conducting Objects in Random Media
Why this work is in the frame
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Bibliographic record
Abstract
Over the last two decades, accurate methods to calculate the intensity of waves backscattering from conducting objects with arbitrary shape in random media were developed successfully. This allowed researchers to analyze numerically the radar cross section (RCS) considering different parameters, such as the configuration of the object and the effects of medium randomness. Data backscattering from the smooth surface of a conducting concave–convex target reveals the obvious impact of its configuration, including size and curvature index on the behavior of RCS. This requires the investigation of the specular reflections, especially in the case of relatively complex contours. We assume wave propagation and scattering from targets in free space and random medium, while considering linear and circular polarizations of incident waves. In this article, we review the backscattering problem and primarily focus on the plane wave as an ideal incident wave in the far field.
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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 | 0.001 | 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 it