Structural Conditions for Model-checking of Parameterized Networks
Bibliographic record
Abstract
Sufficient conditions are given for effective model-checking of parameterized ring networks of isomorphic finite-state processes. Unlike others appearing in the literature, the present sufficient conditions do not restrict the mechanism whereby processes interact with one another, but rather the structure of the processes themselves. The results provide "cutoffs" for systems of "piecewise recognizable" processes, and show that all ring networks based on a given piecewise recognizable template fall into a finite number of weak trace equivalence classes. This result is then extended to three other finer equivalence relations: complete trace equivalence, weak failure equivalence and weak possible-futures equivalence. The paper also formalizes a notion of processes whose actions affect only a bounded number of other processes, using the property of "shuffled processes"; if a ring segment is a shuffled process, then all ring networks fall into a finite number of "weak bisimilarity" classes. It is also shown that each of the above equivalence relations preserve a subset of "observable modal logic" formulas.
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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 | 0.007 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".