Equivalence of Two Types of Knife-Edge Diffraction Models to Predict Shadowing Effect
Bibliographic record
Abstract
The knife-edge diffraction (KED) model has been widely used to predict the shadowing effect. In addition to the classical Fresnel KED model using the Fresnel integral, in recent years an alternative expression proposed by mobile and wireless communications enablers for the twenty-twenty information society (METIS), i.e., METIS KED model, has also been used. This letter proposes a mathematical derivation to rigorously prove that the METIS KED model can be seen as an approximated envelope of the Fresnel KED model. Simulated results agree with the proposal that the METIS KED model is identical to the Fresenl KED model with a low error of 0.19 dB in the shadowed region, and the METIS KED model can be seen as an approximated envelope of the Fresnel KED model with a negligible error of 0.01 dB in the lit region. In addition, based on the connection between the Fresnel and METIS KED models, we propose a threshold for the four-state piecewise linear modeling, which can satisfy the modeling of the shadowing effect at a specific frequency or environment and is the closed form.
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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 | 0.001 | 0.001 |
| 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".