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Record W2088907512 · doi:10.1109/iccse.2014.6926444

Formulation of a state-space model for a parallel manipulator using linear graphs

2014· article· en· W2088907512 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicModeling and Simulation Systems
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsRepresentation (politics)State-space representationState spaceComputer scienceDomain (mathematical analysis)State (computer science)Flow (mathematics)Energy flowSpace (punctuation)Electric power systemSystem dynamicsTopology (electrical circuits)Energy (signal processing)Control theory (sociology)Theoretical computer scienceAlgorithmPower (physics)MathematicsArtificial intelligencePhysicsGeometryMathematical analysis

Abstract

fetched live from OpenAlex

Linear graphs (LGs) present a unified tool for modeling multi-domain dynamic engineering systems. A state space model can be systematically obtained from the LG representation, which is based on energy flow. However, LGs based on energy/power flow cannot properly describe multi-dimensional mechanical systems, while an LG representation of multi-dimensional mechanical systems may not generate a state space model. This paper integrates the two types of LG representation to formulate a state space model for a multidomain engineering system, thereby by heading for a new direction in modeling with LGs.

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 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 score0.509
Threshold uncertainty score0.289

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 head0.083
GPT teacher head0.304
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

Quick stats

Citations0
Published2014
Admission routes2
Has abstractyes

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