MétaCan
Menu
Back to cohort
Record W2755067939 · doi:10.1007/s40279-017-0785-0

The Influence of Growth and Maturation on Stretch-Shortening Cycle Function in Youth

2017· review· en· W2755067939 on OpenAlexaff
John M. Radnor, Jon L. Oliver, Charlotte Waugh, Gregory D. Myer, Isabel S. Moore, Rhodri S. Lloyd

Bibliographic record

VenueSports Medicine · 2017
Typereview
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsStretch shortening cycleUnderpinningAction (physics)Sports medicineSprintPhysical medicine and rehabilitationJumpingPsychologyNeuroscienceMedicinePhysical therapyPhysiologyEngineering

Abstract

fetched live from OpenAlex

Hopping, skipping, jumping and sprinting are common tasks in both active play and competitive sports. These movements utilise the stretch-shortening cycle (SSC), which is considered a naturally occurring muscle action for most forms of human locomotion. This muscle action results in more efficient movements and helps optimise relative force generated per motor unit recruited. Innate SSC development throughout childhood and adolescence enables children to increase power (jump higher and sprint faster) as they mature. Despite these improvements in physical performance, the underpinning mechanisms of SSC development during maturational years remain unclear. To the best of our knowledge, a comprehensive review of the potential structural and neuromuscular adaptations that underpin the SSC muscle action does not exist in the literature. Considering the importance of the SSC in human movement, it is imperative to understand how neural and structural adaptations throughout growth and maturation can influence this key muscle action. By understanding the factors that underpin functional SSC development, practitioners and clinicians will possess a better understanding of normal development processes, which will help differentiate between training-induced adaptations and those changes that occur naturally due to growth and maturation. Therefore, the focus of this article is to identify the potential underpinning mechanisms that drive development of SSC muscle action and to examine how SSC function is influenced by growth and maturation.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.054
GPT teacher head0.340
Teacher spread0.286 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations293
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueSports MedicineSame topicSports Performance and TrainingFrench-language works237,207