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Record W2325643947 · doi:10.1055/s-0034-1368789

Determination of the Optimal Load Setting for Arm Crank Anaerobic Testing in Men and Women

2014· article· en· W2325643947 on OpenAlexaff
Scott C. Forbes, Michael D. Kennedy, N. Boule, Gordon J. Bell

Bibliographic record

VenueInternational Journal of Sports Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsWingate testAnaerobic exerciseCrankMathematicsAnimal sciencePhysical therapyMedicineBiologyGeometry

Abstract

fetched live from OpenAlex

This study compared different relative load factors for eliciting the highest peak 5 s and mean 30 s absolute power output (watts) during an arm crank 30 s Wingate anaerobic power test in 40 upper body trained and recreationally active men and women. The relative load factor of 0.075 kg · kg(- 1) BM elicited a higher peak 5 s power output than 0.070 and 0.080 kg · kg(- 1) for trained males, and 0.070 was higher than 0.055 and 0.080 kg · kg(- 1) for active males (P<0.05). In trained women, the peak 5 s power output was greatest at 0.065 kg · kg(- 1) and 0.060 kg · kg(- 1) for active women. Mean 30 s power output at a relative load factor of 0.060, 0.065 and 0.070 kg · kg(- 1) was higher than 0.080, 0.085 and 0.090 kg · kg(- 1) in trained men, and mean power output at 0.080 kg · kg(- 1) was lower than all other relative load factors in active men (P<0.05). Mean 30 s power was greatest at 0.050 kg · kg(- 1) for trained and active women. In conclusion, the optimal relative load factor was different for eliciting peak 5 s and mean 30 s power outputs during an arm crank Wingate anaerobic test and depends on training status and gender.

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)0.001
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 score0.369
Threshold uncertainty score0.206

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.016
GPT teacher head0.292
Teacher spread0.276 · 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

Citations29
Published2014
Admission routes1
Has abstractyes

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