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Record W2122426387 · doi:10.5555/564124.564214

Web II: web-based simulation of systems described by partial differential equations

2001· article· en· W2122426387 on OpenAlexaff
Manuel Alfonseca, Juan de Lara, Hans Vangheluwe

Bibliographic record

VenueWinter Simulation Conference · 2001
Typearticle
Languageen
FieldDecision Sciences
TopicSimulation Techniques and Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputer scienceCompilerPolygon meshJavaGenerator (circuit theory)Programming languagePartial differential equationSBMLObject-oriented programmingWeb applicationCode (set theory)The InternetCode generationComputational scienceObject (grammar)Distributed computingXMLOperating systemComputer graphics (images)Artificial intelligence

Abstract

fetched live from OpenAlex

This paper describes how to take advantage of Internet services and object technology to solve 2D partial differential equations (PDEs) in a distributed manner. This is accomplished by means of a distributed object oriented continuous simulation language designed by our research group, called OOCSMP, and a Java (and C++) generating compiler for this language (called C-OOL). We also describe a graphical mesh generator, which produces OOCSMP code. The mesh generator may be invoked from the simulation model allowing the generation of domains and meshes during model execution. The simulation of the heating of several moving pieces is shown, in the single machine case, and in the distributed case.

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)0.000
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.154
GPT teacher head0.396
Teacher spread0.242 · 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
GenreMethods

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

Citations9
Published2001
Admission routes1
Has abstractyes

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