A new 3D Gaussian beams launching and predicting model in complex metropolis environment
Bibliographic record
Abstract
The traditional Gaussian beam tracing and predicting model doesn't take a special treatment of diffraction effects,which are accounted for by superposition of transformed beam fields.A new 3D Gaussian beam-tracing and predicting model in complex metropolis environment is proposed.The beam tracing algorithm is based on geometrical optics and the uniform geometrical theory of diffraction.Diffraction effects are evaluated by using complex ray formulas and a new heuristic uniform diffraction coefficient for nonperfectly conducting wedges.The effects of propagation distance and order of reflection on predicting precision and complexity are also analyzed.The simulation results show that the precision of our new method is 0.02 to 2.2dB higher than old Gaussian beam-tracing method and meanwhile the calculation efficiency is decreased by 7.5 to 10 percent in Ottawa.And it is found that 12 is a good value for the order of reflection considering reflection loss and beam transverse extension.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".