Modeling and Characterization of Traffic in Public Safety Wireless Networks
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we present statistical analysis of traffic in a deployed circuit-switched, trunked cellular wireless network used by public safety agencies. Prior analysis considered traffic from three busy hours during two days in 2001. Traffic data in this study span various time periods in 2001, 2002, and 2003. We examine the statistical distribution and autocorrelation function of call inter-arrival and call holding times during several busy hours. We find that call interarrival times are long-range dependent and may be modeled by both Weibull and gamma distributions. Call holding times follow the lognormal distribution and are uncorrelated. These findings indicate that traditional Erlang models for voice traffic may not be suitable for evaluating the performance of trunked radio networks. 1.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it