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Record W2162555555 · doi:10.1109/acc.2007.4282824

Blocking in Parameterized Networks of Discrete-Event-Systems

2007· article· en· W2162555555 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of the ... American Control Conference/Proceedings of the American Control Conference · 2007
Typearticle
Languageen
FieldComputer Science
TopicFormal Methods in Verification
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBlocking (statistics)Undecidable problemDecidabilityParameterized complexityComputer scienceTheoretical computer scienceProcess (computing)Class (philosophy)Component (thermodynamics)Distributed computingAlgorithmComputer networkArtificial intelligence

Abstract

fetched live from OpenAlex

The problem of checking blocking is addressed for two different types of networks that are fully connected, in the graph-theoretic sense. In the first framework, a network consists of an arbitrary number of identical processes and a possibly distinguished control process. Their communication is according to Milner's calculus of communicating systems (CCS). It is shown that the problems of testing such networks for two kinds of blocking, component blocking (CBP) and network blocking (NBP), are decidable. The results are also extended to networks consisting of a finite number of process classes where each class contains an arbitrary number of identical processes. In the second framework, networks consist of isomorphic processes; i.e., all processes are obtained from a unique template by appropriate relabelling. This framework differs from the previous one because processes are distinguishable. It is shown that the halting problem can be reduced to CBP and NBP of such networks, and therefore, they are undecidable.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.004
Science and technology studies0.0000.004
Scholarly communication0.0000.001
Open science0.0070.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.267
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it