Bibliographic record
Abstract
The M/G/1 queue is analyzed by means of a Markov chain imbedded at times of message departure from the system. As in the previous chapter the probability generating function is the mechanism for obtaining results on performance. The primary result is the Laplace transform of the probability density of message delay. This result leads directly to the Pollaczek-Khinchin formula for the average delay in M/G/1 queue. An analysis based on the concept of residual life provides an alternative derivation of this result. These same results are also derived for the case when message that arrive to an empty system receive different service. The next section provides a derivation of the mean and the Laplace transform for the duration of the busy period of the M/G/1 queue. In contrast, we next deal with the G/M/1 queue obtaining the steady state probabilities of the number of messages encountered by an arrival. The final topic treated is priority queue, both preemptive and non-pre-emptive. The results are applied to LANs with the ring topology.
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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 | 0.001 | 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".