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Record W2794872054 · doi:10.1111/sms.13089

Differences in in vivo muscle fascicle and tendinous tissue behavior between the ankle plantarflexors during running

2018· article· en· W2794872054 on OpenAlexaff
Adrian Lai, Glen A. Lichtwark, Anthony G. Schache, Marcus G. Pandy

Bibliographic record

VenueScandinavian Journal of Medicine and Science in Sports · 2018
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsSimon Fraser University
FundersAustralian Research Council
KeywordsFascicleAnkleTendonMuscle architectureAnatomyGastrocnemius muscleSoleus muscleSkeletal muscleMedicine

Abstract

fetched live from OpenAlex

The primary human ankle plantarflexors, soleus (SO), medial gastrocnemius (MG), and lateral gastrocnemius (LG) are typically regarded as synergists and play a critical role in running. However, due to differences in muscle-tendon architecture and joint articulation, the muscle fascicles and tendinous tissue of the plantarflexors may exhibit differences in their behavior and interactions during running. We combined in vivo dynamic ultrasound measurements with inverse dynamics analyses to identify and explain differences in muscle fascicle, muscle-tendon unit, and tendinous tissue behavior of the primary ankle plantarflexors across a range of steady-state running speeds. Consistent with their role as a force generator, the muscle fascicles of the uniarticular SO shortened less rapidly than the fascicles of the MG during early stance. Furthermore, the MG and LG exhibited delays in tendon recoil during the stance phase, reflecting their ability to transfer power and work between the knee and ankle via tendon stretch and storage of elastic strain energy. Our findings add to the growing body of evidence surrounding the distinct mechanistic functions of uni- and biarticular muscles during dynamic movements.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.238

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.018
GPT teacher head0.261
Teacher spread0.243 · 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 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

Citations58
Published2018
Admission routes1
Has abstractyes

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Same venueScandinavian Journal of Medicine and Science in SportsSame topicMuscle activation and electromyography studiesFrench-language works237,207