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Record W2000080668 · doi:10.1055/s-0030-1268412

Thigh Muscle Activities in Elite Rowers During On-Water Rowing

2010· article· en· W2000080668 on OpenAlexaff
Arnaud Guével, Sébastien Boyas, V. Guihard, C Cornu, François Hug, Antoine Nordez

Bibliographic record

VenueInternational Journal of Sports Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsRowingMedicinePhysical medicine and rehabilitationPhysical therapyEliteLeg muscleGeography

Abstract

fetched live from OpenAlex

This study analysed the muscle activity levels and patterns of the major thigh muscle activation during training sections at different intensities of on-water rowing. 9 experienced rowers performed 2 imposed-pace sections (B1 and B2) and 2 maximal-speed sections (start, 500 m) of on-water rowing. The knee angle, power output, mean torque and stroke rate were measured using specific instrumentation and were synchronised with surface electromyography signals of 5 superficial quadriceps and hamstring muscles. B1 and B2 sections were not significantly different regarding mechanical parameters and EMG activities, while the start phase induced large differences. The EMG patterns for B1, B2 were similar (cross-correlation coefficients (CC) ranged between 0.972-0.984) and the moderate CC found between both B1 and start (0.605-0.720) and B2 and start (0.629-0.720). Our results suggest that the hamstring muscles have a motor action and contribute to the power production during the leg drive. During an all-out 500 m section, a decrease in power and stroke rate was found (up to 20%). However, EMG patterns were not time shifted for all muscles. During the leg drive, the muscle activity levels of the quadriceps muscles were unchanged, while the activity of the hamstring muscles decreased.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.282
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.

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

Citations32
Published2010
Admission routes1
Has abstractyes

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