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Record W2090855143 · doi:10.1080/00222890903269237

The Effect of Knee Joint Angle on Torque Control

2010· article· en· W2090855143 on OpenAlexaff
Jacob J. Sosnoff, Stefani J. Voudrie, Kyle T. Ebersole

Bibliographic record

VenueJournal of Motor Behavior · 2010
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsCentre for Movement Disorders
FundersNational Center for Advancing Translational Sciences
KeywordsTorqueKnee JointKnee flexionMathematicsPhysical medicine and rehabilitationStandard deviationJoint (building)Coefficient of variationOrthodonticsMedicinePhysicsStatisticsSurgeryEngineeringStructural engineering

Abstract

fetched live from OpenAlex

The purpose of the author's investigation was to examine the effect of knee joint angle on torque control of the quadriceps muscle group. In all, 12 healthy adults produced maximal voluntary contractions and submaximal torque (15, 30, and 45% MVC [maximal voluntary contraction]) at leg flexion angles of 15 degrees , 30 degrees , 60 degrees , and 90 degrees below the horizontal plane. As expected, MVC values changed with respect to joint angle with maximum torque output being greatest at 60 degrees and least at 15 degrees . During the submaximal tasks, participants appropriately scaled their torque output to the required targets. Absolute variability (i.e., standard deviation) of torque output was greatest at 60 degrees and 90 degrees knee flexion. However, relative variability as indexed by coefficient of variation (CV) decreased as joint angle increased, with the greatest CV occurring at 15 degrees . These results are congruent with the hypothesis that joint angle influences the control of torque.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
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)0.0020.000

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 head0.005
GPT teacher head0.215
Teacher spread0.210 · 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 designObservational
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

Citations21
Published2010
Admission routes1
Has abstractyes

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