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Record W2042739968 · doi:10.1139/h2012-020

Neuromuscular fatigue recovery following rapid and slow stretch–shortening cycle movements

2012· article· en· W2042739968 on OpenAlexafffundvenue
Katie P. Wadden, Duane C. Button, Armin Kibele, David G. Behm

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2012
Typearticle
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaMemorial University of Newfoundland
KeywordsPhysical medicine and rehabilitationStretch shortening cycleMedicineJumping

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate underlying mechanisms and neuromuscular recovery patterns following rapid and slow stretch-shortening cycle (SSC) movements performed to fatigue. Fourteen (10 moderately trained (MT) and four highly trained (HT)) subjects completed rapid and slow SSC movements to fatigue. The rapid SSC movement consisted of continuous drop jumps from a 30 cm platform until a predetermined jump height was no longer maintained, and the slow SSC movement consisted of continuous squats to 90° of knee flexion at a load of 65% of subject's one-repetition maximum until no further repetitions could be completed. Although blood lactate measures were significantly (p < 0.002) higher after the rapid SSC condition versus after the slow SSC condition, the recovery of neuromuscular properties (maximum voluntary contractions, twitch force, muscle compound action potential) following the two conditions to fatigue did not differ. The duration of the rapid SSC movement was dependent on the training status of the subject; HT subjects performed the rapid SSC longer (68.2%) than the MT subjects until fatigued. Thus, the neuromuscular fatigue recovery patterns were independent of the type of SSC movement, condition duration, and subject training status. Because rapid and slow SSC exercises induce similar fatigue patterns, training programs incorporating rapid SSC exercises can be developed similar to that prescribed in traditional slow SSC resistance training programs.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score0.694

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.023
GPT teacher head0.275
Teacher spread0.252 · 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 designBench or experimental
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

Citations19
Published2012
Admission routes3
Has abstractyes

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