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Record W2610034514 · doi:10.3389/fphys.2017.00247

Calf Compression Sleeves Change Biomechanics but Not Performance and Physiological Responses in Trail Running

2017· article· en· W2610034514 on OpenAlexaff
Hugo A. Kerhervé, Pierre Samozino, Fabrice Descombe, M. Pinay, Guillaume Y. Millet, Marion Pasqualini, Thomas Rupp

Bibliographic record

VenueFrontiers in Physiology · 2017
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBiomechanicsCompression (physics)Physical medicine and rehabilitationMedicineAnatomyMaterials science

Abstract

fetched live from OpenAlex

Introduction: The aim of this study was to determine whether calf compression sleeves (CS) affects physiological and biomechanical parameters, exercise performance, and perceived sensations of muscle fatigue, pain and soreness during a prolonged (~2 h 30 min) outdoor trail running. Methods: Fourteen healthy trained males took part in a randomized, cross-over study consisting in two identical 24-km trail running sessions (each including one bout of running at constant rate on moderately flat terrain, and one period of all-out running on hilly terrain) wearing either degressive CS (23 ± 2 mmHg) or control sleeves (CON, 6 on a 10-cm scale) with no difference between conditions. However, Achilles tendon pain was significantly lower after the trial in CS than CON (p < 0.05). Discussion: Calf compression did not modify muscle oxygenation during ~2h30 of trail running but significantly changed running biomechanics and lower limb muscle functional capabilities toward a more dynamic behavior compared to control session. However, wearing compression sleeves did not affect performance and exercise-induced DOMS, while it minimized Achilles tendon pain immediately after running.

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 score0.275
Threshold uncertainty score0.612

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 head0.084
GPT teacher head0.314
Teacher spread0.230 · 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

Citations46
Published2017
Admission routes1
Has abstractyes

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