Conjunctive and Disjunctive Architectures for Decentralized Prognosis of Failures in Discrete-Event Systems
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Bibliographic record
Abstract
Kumar and Takai have proposed an architecture for the decentralized prognosis of discrete-event systems (DES), where several local prognosers cooperate to predict failures in a DES. In this paper, we first present the proposition (Kumar and Takai, "Decentralized prognosis of failures in discrete event systems," IEEE Trans. Autom. Control, vol. 55, no. 1, pp. 48-59, Jan. 2010) as a disjunctive architecture, and then we develop a conjunctive architecture which is dual and complementary to the disjunctive one. We also propose a mixed architecture that combines and generalizes the disjunctive and conjunctive architectures. We finally show that our work can be easily extended to predict a failure at least k steps before its occurrence, for a given k >; 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 | 0.001 | 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 | 0.000 | 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