A Novel Approach to Determine Minimal Tie-Sets of Complex Network
Why this work is in the frame
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Bibliographic record
Abstract
Network reliability analysis is usually based on minimal path or cut enumeration from which the associated reliability expressions are deduced. The cut-set method is a popular approach in the reliability analysis of many systems from simple to complex configurations. The computational requirements necessary to determine the minimal cut-sets of a network depend mainly on the number of minimal paths between the source and the sink. A technique designated as the "Path Tracing Algorithm" is presented in this paper, which can handle both simple and complex networks, and considers both unidirectional and bi-directional branches. A step by step procedure is explained using a bridge-network. The algorithm is easy to program, and does not require limits on the size of the network. The applicability of the proposed technique is illustrated by application to a more complicated system.
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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 | 0.000 |
| 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