MétaCan
Menu
Back to cohort
Record W2547009193 · doi:10.1139/tcsme-2010-0010

THE SYNTHESIS OF MECHANISM SYSTEMS USING A MECHANISM CONCEPT LIBRARY

2010· article· en· W2547009193 on OpenAlexvenueno aff
Feng-Ming Ou, Hong‐Sen Yan, Ming‐Feng Tang

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2010
Typearticle
Languageen
FieldComputer Science
TopicModel-Driven Software Engineering Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsKinematicsMechanism (biology)Computer scienceGraphConstructiveMechanism designRepresentation (politics)Theoretical computer scienceMathematicsProgramming language

Abstract

fetched live from OpenAlex

This paper presents an approach for synthesizing all possible mechanism systems of kinematic building blocks in a mechanism concept library. The kinematic building blocks are defined as SISO primitive mechanisms, and their serial and/or parallel combinations are expressed as corresponding out-trees based on graph representation. By representing the constructive building blocks as labeled vertices and their possible combination relationships as directed edges, the synthesis approach is developed by adopting graph enumeration theorem. An illustrative example of four kinematic building blocks, including two crank-rocker linkages and two slider-crank mechanisms, is provided to validate the presented approach. The result shows that all feasible mechanism systems can be obtained effectively by following the synthesis method and which provides more alternatives in the library during design or re-design of mechanisms.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.010
GPT teacher head0.196
Teacher spread0.186 · 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 designTheoretical or conceptual
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
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicModel-Driven Software Engineering TechniquesFrench-language works237,207