Reliability Evaluation of Imperfect K-Terminal Stochastic Networks using Polygon-to Chain and Series-parallel Reductions
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Bibliographic record
Abstract
In this paper, we propose a mathematical model for determining the exact value of the reliability of Mobile Ad hoc (MANET) and Wireless Sensor (WSN) Networks which are considered in this research as a collection of Imperfect Stochastic Networks (ISN). The performance in term of reliability is a fundamental challenge in ISN. In the literature several techniques have been used for determining the reliability and few of them are able to produce exact values. The aim of this work introduces a general framework that extends and combines two major models proposed by Satyanarana and Wood, and Carlier and Theologou. These models are based on the reduction using the factoring theorem. The operations of reduction are called Polygon-to Chain and series-parallel decompositions. The algorithm is also very effective for imperfect networks whose nodes and links could fail.
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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 | 0.001 | 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 it