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Record W1506968675 · doi:10.1002/mus.24342

Neuromuscular fatigue of the knee extensors during repeated maximal intensity intermittent‐sprints on a cycle ergometer

2014· article· en· W1506968675 on OpenAlexaff
Gregory E. P. Pearcey, Justin R. Murphy, David G. Behm, Dean C. Hay, Kevin E. Power, Duane C. Button

Bibliographic record

VenueMuscle & Nerve · 2014
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsNipissing UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsSprintMedicinePhysical medicine and rehabilitationMuscle fatiguePhysical therapyCardiologyElectromyography

Abstract

fetched live from OpenAlex

INTRODUCTION: We studied the time course of neuromuscular fatigue during maximal intensity intermittent-sprint cycling. METHODS: Eight participants completed 10, 10-s sprints interspersed with 180 s of recovery. The power outputs were recorded for each sprint. Knee extensor maximum voluntary contraction (MVC) force, voluntary activation, and evoked contractile properties were recorded presprint, postsprint 5, and postsprint 10. RESULTS: Total work over the 10 sprints decreased significantly (P < 0.05) and could be described by 2 linear relationships from sprints 1-5 compared with sprints 6-10. Participants had significantly (P < 0.05) lower MVC and twitch forces postsprint 5 compared with presprint. MVC, voluntary activation, and twitch force were decreased (P < 0.05) postsprint 10 compared with postsprint 5. CONCLUSIONS: The maximal intermittent sprints induced neuromuscular fatigue. Neuromuscular fatigue in the first 5 sprints was mainly peripheral, whereas in the last 5 sprints it was both peripheral and central.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.507

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 head0.020
GPT teacher head0.243
Teacher spread0.223 · 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

Citations38
Published2014
Admission routes1
Has abstractyes

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