On the relevance of two‐dimensional models for radiation of statistical sources in stratified media
Bibliographic record
Abstract
Abstract We present analytical closed‐form expressions for the radiation patterns of 2‐D line sources and 3‐D point dipoles embedded in a general multilayered configuration. While the former are simplified model sources, used as a preliminary analytical step to reduce derivation complexity, the latter have been shown experimentally to reproduce the electromagnetic behavior of many elementary statistical sources. By decomposing the sources to current elements generating pure transverse electric (TE) or transverse magnetic (TM) polarized radiation, we arrive at a unified format for the radiation pattern expression for all sources considered. Analyzing the common 1‐D (characteristic) Green's function, we show that the normalized TE‐polarized emission of model 2‐D electric line sources reproduces exactly the measured TE‐polarized radiation of statistical (3‐D) dipoles with random in‐plane orientation; the connection between the TM‐polarized emission of the two species is discussed, and physical interpretation is provided via the unified expression. These results specify the precise relations between the 2‐D and 3‐D models, providing intuition as well as guidelines for proper usage of simplified 2‐D results for analysis of realistic 3‐D statistical configurations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".