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Record W2053045226 · doi:10.1519/r-15634.1

Effect of Loading on Enhancement of Power Performance Over Three Consecutive Trials

2005· article· en· W2053045226 on OpenAlexaff
Daniel Robbins, David Docherty

Bibliographic record

VenueThe Journal of Strength and Conditioning Research · 2005
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSquatIsometric exerciseCountermovementMathematicsMedicineStatisticsPower (physics)Physical therapyAnimal sciencePhysicsJump

Abstract

fetched live from OpenAlex

The acute effects of maximal voluntary isometric contractions (MVICs) in the squat position on subsequent measures of power output over 3 consecutive sets were investigated. Sixteen trained men experienced with back squats participated in the study. A 7-second MVIC was performed 4 minutes before the execution of 5 maximal countermovement jumps (CMJs) and was repeated for 3 consecutive sets (protocol 1). The results were compared to power output performance in a similar protocol (protocol 2) that excluded the 7-second MVICs. No significant differences occurred in any of the power output measurements between protocol 1 and protocol 2, nor did significance occur linearly across the 4 sets of CMJ, with the exception of a decrease in peak power in protocol 2 (p < or = 0.05). Using both mean and maximal values only one significant correlation between either relative strength and performance enhancement or absolute strength and performance enhancement was present at p < or = 0.01. At p < or = 0.05, significant correlations were found between absolute strength and mean peak power (PP), mean peak acceleration (PA), mean peak force (PF), max PP, max PA, max PF, and max peak velocity. These data indicate that the execution of an MVIC performed before a power exercise was inadequate to acutely enhance power output over any of 3 consecutive trials.

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)0.007
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
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 head0.051
GPT teacher head0.397
Teacher spread0.346 · 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 designBench or experimental
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

Citations64
Published2005
Admission routes1
Has abstractyes

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