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Record W5579926

VIRTUAL PROTOTYPING OF REACTIVE SYSTEMS IN SIDE

2010· article· en· W5579926 on OpenAlexaff
Paweł Gburzyński, Jacek Maitan, Larry Hillyer

Bibliographic record

VenueArchivum chirurgicum neerlandicum · 2010
Typearticle
Languageen
FieldEngineering
TopicAdvanced Data Processing Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComputer scienceVirtual prototypingHuman–computer interactionSimulation
DOInot available

Abstract

fetched live from OpenAlex

We introduce a software package, called SIDE, 1 for developing and executing control programs driving distributed reactive systems. One distinctive feature of SIDE is that it can be used as a simulator: some (or even all) components of the underlying physical system can be virtual, which makes it possible to develop the control program together with the physical system to be controlled. SIDE applications can be naturally distributed and interconnected via the Internet. In particular, control programs in SIDE can be monitored and operated from remote locations via Java applets invoked from web pages. Introduction Many real-time systems used in automated manufacturing or industrial process control depend on the use of sensors and actuators interconnected by networks. Traditionally, such networks have been highly specialized, with their hardware and software dedicated to their specific purpose. This approach was a consequence of the highly local character of these networks: there was ...

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.006
GPT teacher head0.229
Teacher spread0.223 · 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 designSimulation or modeling
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

Citations2
Published2010
Admission routes1
Has abstractyes

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