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Record W2031775405 · doi:10.1519/jsc.0b013e318207ef37

Repeated-Sprint Ability and Aerobic Fitness

2011· article· en· W2031775405 on OpenAlexaffabout
Nicolas Thébault, L Léger, Philippe Passelergue

Bibliographic record

VenueThe Journal of Strength and Conditioning Research · 2011
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsSprintAerobic exerciseMulti-stage fitness testMathematicsJumpingAnaerobic exerciseFitness testStatisticsPhysical fitnessPhysical therapyMedicine

Abstract

fetched live from OpenAlex

The purpose of this study was to reinvestigate the relationship between aerobic fitness and fatigue indices of repeated-sprint ability (RSA), with special attention to methodological normalization. Soldiers were divided into low (n = 10) and high (n = 9) fitness groups according to a preset maximal aerobic speed (MAS) of 17 km·h(-1) (∼60 ml O2·kg(-1)·min) measured with the University of Montreal Track Test (UMTT). Subjects' assessment included the RSA test (3 sets of 5 40-m sprints with 1-minute rest between sprints and 1.5 minutes between sets), a 40-m sprint (criterion test used in the computation of fatigue indices for the RSA test), strength and power measurement of the lower limbs, and the 20-m shuttle run test (20-m SRT) and the UMTT, which are measures of maximal aerobic power. The highest correlation with the RSA fatigue indices was obtained with the 20-m SRT (r = 0.90, p = 0.0001, n = 19), a test with 180° direction changes and accelerations and decelerations. The lower correlation (r = 0.66, p < 0.01, n = 19) with the UMTT (continuous forward running) suggests that some aerobic tests better disclose the importance of aerobic fitness for RSA and that aerobic power is not the sole determinant of RSA. However, neither strength nor vertical jumping power was correlated to the RSA fatigue indices. Subjects with greater MAS were able to maintain almost constant level of speed throughout series of repeated sprints and achieved better recovery between series. A MAS of at least 17 km·h(-1) favors constant and high speed level during repeated sprints. From a practical point of view, a high aerobic fitness is a precious asset in counteracting fatigue in sports with numerous sprint repetitions.

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)0.002
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 score0.067
Threshold uncertainty score0.226

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.080
GPT teacher head0.352
Teacher spread0.272 · 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

Citations37
Published2011
Admission routes2
Has abstractyes

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