MétaCan
Menu
Back to cohort
Record W2068233561 · doi:10.1055/s-2004-817922

EMG Activity does not Change During a Time Trial in Competitive Cyclists

2005· article· en· W2068233561 on OpenAlexaff
Sébastien Duc, Andrew C. Betik, F. Grappe

Bibliographic record

VenueInternational Journal of Sports Medicine · 2005
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsVastus medialisCadenceBicepsElectromyographyCycle ergometerCyclingTime trialMedicinePhysical medicine and rehabilitationLower limbLeg muscleWork (physics)Physical therapyInternal medicineSurgeryHeart ratePhysicsBlood pressure

Abstract

fetched live from OpenAlex

The purpose of the present study was to measure the electromyographic (EMG) activity of four lower limb muscles and the propulsive torque during a cycling time-trial (TT). Nine competitive cyclists (V.O (2max): 73.8 +/- 5.3 ml . min (-1) . kg (-1)) performed two tests separated over a one-week period on a friction-load cycle ergometer equipped with a SRM crankset scientific system: 1) a continuous incremental test for the determination of the peak power output (PPO); and 2) a 30-min TT test at a self-selected work intensity. The EMG activity of the vastus medialis (VM), the rectus femoris (RF), the biceps femoris (BF), and the gastrocnemius medialis (GAS), and the propulsive torque were recorded every 5 min for 10 s. There was no time effect on the power output, the pedalling cadence, and the mean propulsive torque. The EMG activity of the VM and the RF muscles was unchanged during the TT (p > 0.05). The EMG activity of the two knee flexor muscles (BF and GAS) tended to increase with time but it was not significant (p > 0.05). The EMG/torque of the VM and the RF muscles tended to decrease with time but it was not significant (p > 0.05). The lack of increase in the EMG activity of the four investigated muscles seems to indicate that the subjects performed the TT test at a muscular work steady-state.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.923
Threshold uncertainty score0.349

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 head0.259
Teacher spread0.246 · 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

Citations33
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Sports MedicineSame topicMuscle activation and electromyography studiesFrench-language works237,207