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Record W2163965488 · doi:10.1109/ccece.2005.1557391

Denotational semantics for RTPA

2006· article· en· W2163965488 on OpenAlexaff
Xinming Tan, Yingxu Wang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCognitive Computing and Networks
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsConcurrencyDenotational semanticsComputer scienceProcess calculusInterruptSemantics (computer science)Operational semanticsProgramming languageProcess (computing)Event (particle physics)Denotational semantics of the Actor modelInterval (graph theory)Set (abstract data type)Communicating sequential processesTheoretical computer scienceMathematicsEmbedded system

Abstract

fetched live from OpenAlex

Real-time process algebra (RTPA) is designed to deal with a rich set of fundamental real-time processes such as timing, interrupt, concurrency, and event/time-driven. Some of the RTPA processes cannot be described adequately in conventional denotational semantics paradigms. This paper develops a new framework for modeling time and processes in order to represent RTPA in denotational semantics. Within this framework, time is modeled by elapse of process execution. The process environment encompasses states of all variables, represented as mathematical maps, which project variables to their corresponding values. Duration is introduced as a pair of time interval and the environment to represent the process environment change during a time interval. Temporal ordered durations and operations on them are used to denote process executions. With all these means, the semantics of RTPA processes of timing, interrupt, concurrency, event/time-driven, and traditional sequential processes can be formally expressed.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0050.008
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.002

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 head0.009
GPT teacher head0.225
Teacher spread0.216 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2006
Admission routes1
Has abstractyes

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