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Record W4390655562 · doi:10.47738/ijiis.v7i1.189

Efficient Generation of Models through Swift Assembly Techniques in Computer-Aided Design Systems

2024· article· en· W4390655562 on OpenAlexaff
Yuanzhe Deng

Bibliographic record

VenueIJIIS International Journal of Informatics and Information Systems · 2024
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSwiftComputer scienceComputer-aidedComputer Aided DesignSystems engineeringEngineering drawingEngineeringOperating systemProgramming language

Abstract

fetched live from OpenAlex

Rapid assembly modeling system is a tool that needs to be used in the design process. Because the three-dimensional modeling is intuitive, powerful and can be used in actual engineering, it is more and more used in manufacturing production. In the rapid development of computer-aided design technology, CAD/CAM software is the most commonly used and most widely used modeling tool. Therefore, the purpose of this article to study the rapid assembly modeling in the computer-aided design system is to improve the performance and accuracy of the assembly system and promote the high-quality production of products. This article mainly uses experimental method and case analysis method to test the assembly system designed in this article. The experimental results show that, under low temperature conditions, the relative error and absolute error of the assembly size are in a small space, which meets the actual requirements. Therefore, the system designed in this paper can be used in practice.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.962
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.003
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 head0.024
GPT teacher head0.241
Teacher spread0.217 · 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
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

Citations0
Published2024
Admission routes1
Has abstractyes

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