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Record W2621785541 · doi:10.1115/imece2001/bed-23057

An Equivalent Linkage Model for Understanding Stiffness Effects of Biarticular Muscles

2001· article· en· W2621785541 on OpenAlexaff
Donald Russell, Chad English

Bibliographic record

VenueAdvances in Bioengineering · 2001
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsKinematicsLinkage (software)StiffnessSet (abstract data type)Four-bar linkageComputer scienceDecompositionBiomechanicsStructural engineeringEngineeringPhysicsAnatomyArtificial intelligenceClassical mechanicsChemistryMedicine

Abstract

fetched live from OpenAlex

Abstract The purpose of this paper is to describe a method for aiding in the intuitive understanding of the effects of bi-articular muscles on the stiffness of a limb. In particular, a kinematic analysis of a mechanical model of a human arm is performed. The results are manipulated into a form that makes evident a mathematical decomposition of the kinematics. This gives rise to a mechanical analog to the decomposition: an equivalent four-bar linkage with single-joint muscles. Further insight is gained as the equivalent linkage provides an intuitive direction associated with each set of muscles.

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: Empirical · Consensus signal: none
Teacher disagreement score0.720
Threshold uncertainty score0.662

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 head0.021
GPT teacher head0.262
Teacher spread0.242 · 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

Citations1
Published2001
Admission routes1
Has abstractyes

Explore more

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