Background data service for cellular mobile radio
Bibliographic record
Abstract
The idea of background data service (BDS) is to use the idle times between voice calls in a cellular system for data transmission by conventional cellular transceivers with attached modems with no requirement for media-access contention protocols in the mobiles. When studied from this viewpoint, there appears to be useful capacity available for exploitation without impact on the foreground voice telephony system. Strategies for data session displacement and assignment can shape the distributions of active and inactive durations to suit the applications to a certain degree. The most promising approach seems to be time-sharing among sessions and the use of priorities to create permanent data sessions with a range of availabilities. Using enforced time-sharing with /spl Delta/T = 5 s, it is possible to obtain an average active time of 5.77 s after an average of only 6.77 s of inactivity for 8 equal-priority sessions in a 15 channel system loaded to 10% blocking, i.e., overloaded with voice traffic.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.007 | 0.002 |
| 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".