Bibliographic record
Abstract
The estimation of the coverage area of a single transmitter in a microcell environment with irregular distribution and elevation of buildings is investigated in this paper. Two methods were applied to compute the coverage area of five locations of a test transmitter. The first method corresponded to a simple thresholding of the estimated path loss values provided by a deterministic propagation prediction model based on physical optics and the Geometrical Theory of Diffraction (GTD). We propose a second method to compute the coverage area based on a set of heuristic rules that combines the estimated values of the propagation path loss, information from the environment as well as data from physical measurements. We performed extensive signal strength measurements in order to evaluate the accuracy of the estimation of the coverage area. According to our results, computing the coverage area by applying a threshold to the predicted path loss values leads to significant errors, in average 20% of the map was erroneously included in the coverage area of each test location of the transmitter. We were able to reduce this error to 4% with our proposed method based on heuristic rules.
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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 | 0.000 | 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 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".