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Record W2889094875 · doi:10.5430/wje.v8n4p111

The Comparison of Lower Extremity Isokinetic Strength in Volleyball Players According to the Leagues

2018· article· en· W2889094875 on OpenAlexvenueno aff
Cengiz Akarçeşme, Sinem Hazır Aytar

Bibliographic record

VenueWorld Journal of Education · 2018
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsnot available
Fundersnot available
KeywordsHamstringLeagueJumpingPhysical therapyMuscle strengthPsychologyPhysical medicine and rehabilitationIsometric exerciseMedicinePhysics

Abstract

fetched live from OpenAlex

The purpose of the study is to compare the ratio of lower extremity isokinetic hamstring/quadriceps ratio (H/Q),bilateral strength difference (BLD) and relative peak torques (RPT) in volleyball players according to the leagues.101 volleyball players participated in the study (female=34, male=25 from 1st league; female=21, male=21 from 2ndleague). Isokinetic extension and flexion of knee muscle strengths of the volleyball players were determined withisokinetic dynamometer. Independent t test was used to compare volleyball players' flexor and extensor RPT, H/Qratios and BLD according to their leagues. In the study conducted, it was determined that both male and femalevolleyball players playing the 1st league had higher RPTs at 60°s-1 and 180°s-1 angular velocities. It was determinedthat volleyball players’ BLD was within the desired limits, whereas their H/Q ratios were low. As a result, it wasdetermined that the lower extremity isokinetic knee muscle RPT of the volleyball players playing in the 1st Leaguehad better values than those playing in the 2nd league, but these values were higher in the extension RPT. Since theessential requirement of volleyball is the jumping strength of the movements, this case may be related to the greaterdevelopment of the extensor muscles.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.136

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.029
GPT teacher head0.358
Teacher spread0.329 · 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

Citations5
Published2018
Admission routes1
Has abstractyes

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