Bibliographic record
Abstract
This paper disproves an hypothesis that this author had made in an earlier paper from the observation that the values of the plane wave scattering coefficients computed with his numerical method could vary substantially with the physical separation distance between the integration box and the scatterer enclosed within the box. This variation was observed when the edges and corners of the integration box were strongly illuminated with the scattered field. It was hypothesized that this variation was due to the use of a box as the integration surface because a box is not the smooth integration surface that is supposed to be needed for the application of Huygens' principle on which is based the computation of the far-field values with the steady-state near-to-far field transformation. In this paper, it is found by reconstructing the spatial field distribution that corresponds to the error spectrum, and noting that this distribution is not confined to the edges and corners of the integration box, that the use of the box is not the cause for the variation and thus, that the hypothesis is false. It turned out that the variation nearly disappeared when the FDTD mesh size was of the order of 100 cells per wavelength. It is shown that the variation was due to the second-order accuracy of the FDTD stencil.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".