MétaCan
Menu
Back to cohort
Record W4398235020 · doi:10.1242/bio.060383

A methodological approach for collecting simultaneous measures of muscle, aponeurosis, and tendon behaviour during dynamic contractions

2024· article· en· W4398235020 on OpenAlexafffund
Stephanie A. Ross, Christine Waters‐Banker, Andrew Sawatsky, T.R. Leonard, Walter Herzog

Bibliographic record

VenueBiology Open · 2024
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaKillam Trusts
KeywordsAponeurosisIsometric exerciseSonomicrometryTendonFascicleAnatomyMuscle bellyBiologyContraction (grammar)Muscle contractionBiomedical engineeringMedicineCarnivora

Abstract

fetched live from OpenAlex

Skeletal muscles and the tendons that attach them to bone are structurally complex and deform non-uniformly during contraction. While these tissue deformations dictate force production during movement, our understanding of this behaviour is limited due to challenges in obtaining complete measures of the constituent structures. To address these challenges, we present an approach for simultaneously measuring muscle, fascicle, aponeurosis, and tendon behaviour using sonomicrometry. To evaluate this methodology, we conducted isometric and dynamic contractions in in situ rabbit medial gastrocnemius. We found comparable patterns of strain in the muscle belly, fascicle, aponeurosis, and tendon during the isometric trials to those published in the literature. For the dynamic contractions, we found that our measures using this method were consistent across all animals and aligned well with our theoretical understanding of muscle-tendon unit behaviour. Thus, this method provides a means to fully capture the complex behaviour of muscle-tendon units across contraction types.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.121
GPT teacher head0.348
Teacher spread0.228 · 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 designBench or experimental
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

Citations6
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueBiology OpenSame topicMuscle activation and electromyography studiesFrench-language works237,207