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Record W2800277960 · doi:10.1139/tcsme-2004-0012

CAD DATA EXTRACTION FOR SIMULATION: AN APPLICATION IN CAMERA VIEW MODELLING

2004· article· en· W2800277960 on OpenAlexaffvenue
Chandan Joardar, Leila Notash

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsQueen's University
Fundersnot available
KeywordsCADComputer scienceJavaComputer Aided DesignSoftwareClass (philosophy)Engineering drawingASCIIData model (GIS)VisualizationSolid modelingComputational geometryData structureComputer graphics (images)Data miningProgramming languageArtificial intelligenceEngineeringOperating system

Abstract

fetched live from OpenAlex

CAD systems are generally well specified and appropriate to relevant applications but do not support unspecified extension of applications. With the purpose of extending applications of CAD models beyond the stipulated limit, efforts have been made in this study to develop a utility to extract and use the geometry data from CAD models. A software tool has been developed in Java to extract the geometry data of 3D CAD models from its ASCII format IGES translations. The extracted geometry data have been used to populate a data structure of a Java class that resembles a solid model. Objects of this Java class have been used to develop some visual modelling manipulation operations. A database has been developed to store the geometry data for subsequent applications. This study to extract the geometry data of CAD models was motivated in view of its extension to a larger research work on a robot assisted visual inspection system.

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 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 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: none
Teacher disagreement score0.928
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.028
GPT teacher head0.250
Teacher spread0.221 · 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 teacher head, 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

Citations1
Published2004
Admission routes2
Has abstractyes

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