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Record W2034589391 · doi:10.1139/h09-125

An investigation into the possible physiological mechanisms associated with changes in performance related to acute responses to different preactivity stretch modalities

2010· article· en· W2034589391 on OpenAlexvenueno aff
Iain M. Fletcher, Mathew M. Monte-Colombo

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2010
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsnot available
Fundersnot available
KeywordsCountermovementElectromyographyHeart rateMedicineCore (optical fiber)CardiologyCore temperatureJumpPhysical medicine and rehabilitationInternal medicineMaterials sciencePhysicsBlood pressure

Abstract

fetched live from OpenAlex

The aim of this study was to explore the potential mechanisms underlying performance changes linked to different warm-up stretch modalities. Twenty-one male collegiate-semiprofessional soccer players (age, 20.8 +/- 2.3 years) performed under 3 different warm-up conditions: a no-stretch warm-up (WU), a warm-up including static passive stretches (SPS), and a warm-up incorporating static dynamic stretches (SDS). Countermovement jump, drop jump, peak torque, heart rate, core temperature, movement kinematics, and electromyography (EMG) were recorded for each intervention. Significant increases (p < 0.001) in performance were recorded for the countermovement, drop jump, and peak torque measures when the SDS was compared with the WU and SPS trials. When mechanism data were analysed, heart rate was significantly higher (p < 0.001) in the SDS condition compared with the SPS and WU conditions (a pattern also shown with core temperature), whereas the WU condition heart rate was also significantly higher than the SPS condition heart rate. When EMG data were examined for the rectus femoris muscle, significantly greater (p < 0.01) muscle activity was observed in the SDS condition compared with the SPS condition. It seems the most likely mechanisms to explain the increase in performance in the SDS condition compared with the SPS condition are increased heart rate, greater muscle activity, and increased peak torque.

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 score0.899
Threshold uncertainty score0.450

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 head0.013
GPT teacher head0.267
Teacher spread0.254 · 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

Citations67
Published2010
Admission routes1
Has abstractyes

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