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Record W2594035361 · doi:10.1109/antem.2004.7860675

A preliminary approach to simulate parallel mesh refinement with Petri nets for 3-D finite element electromagnetics

2004· article· en· W2594035361 on OpenAlex
Da Qi Ren, Dennis D. Giannacopoulos

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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicPetri Nets in System Modeling
Canadian institutionsMcGill University
Fundersnot available
KeywordsPetri netComputer scienceFinite element methodParallel computingComputational scienceMesh generationElectromagneticsSoftwareDiscrete event simulationComputational electromagneticsParallel algorithmEvent (particle physics)AlgorithmComputer engineeringDistributed computingTheoretical computer scienceSimulationProgramming languageEngineeringElectronic engineeringElectromagnetic fieldStructural engineering

Abstract

fetched live from OpenAlex

An approach utilizing Petri Nets for modeling and evaluating parallel, unstructured mesh refinement is developed. A model is implemented based on a detailed software prototype and system architecture, which mimics the behavior of the parallel meshing. Subsequently, estimates for performance measures are derived from discrete event simulations. The potential benefits and related costs of this new approach for developing high performance parallel mesh refinement algorithms are examined.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.380
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.025
GPT teacher head0.251
Teacher spread0.226 · 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

Quick stats

Citations5
Published2004
Admission routes1
Has abstractyes

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