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Record W159939317

TESTING MODALITY IS VITAL TO DETECT PERFORMANCE CHANGES IN OVERREACHING RESISTANCE EXERCISE

2014· article· en· W159939317 on OpenAlexaboutno aff
Justin X. Nicoll, AC Fry, Lzf Chiu, BK Schilling, LW Weiss Facsm

Bibliographic record

VenueTopSCHOLAR (Western Kentucky University) · 2014
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsnot available
Fundersnot available
KeywordsModality (human–computer interaction)Resistance trainingMedicineComputer sciencePhysical therapyArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

Justin Nicoll1, Andrew C. Fry1, Loren Z. F. Chiu2, Brian K. Schilling3 & Lawrence W. Weiss3, FACSM 1University of Kansas, Lawrence, Kansas; 2University of Alberta, Edmonton, Alberta, Canada; 3University of Memphis, Memphis, Tennessee Non-functional overreaching (NFOR) is detrimental to resistance exercise (RE) performance. Research concerning sensitive and sport specific methods that identify NFOR is sparse, and inconsistencies of results may be due to differences in testing modalities. PURPOSE: The purpose of this study was to compare muscle performance using different testing modalities (dynamic vs. isometric) after high power RE overreaching (OR). METHODS: As part of a larger dietary supplementation study, seventeen men (n=17; X±SD; age: 22.8±3.3yrs) were randomly assigned to a supplement (SUPP; n=8; body mass: 88.28±16.7kg; bodyfat: 11.7±6.4%), placebo (PL: n=3; bodymass: 86.66±25.7kg; bodyfat: 12.9±10.8%), or control (CON; n=6; body mass: 76.63±8.4kg, bodyfat: 11.3±6.8%) group. All groups participated in two weeks of normal training. After normal training, SUPP and PL performed OR for one week, while CON continued normal training. External mean power (MP), force (MF), and velocity (MV) were determined for the barbell squat exercise at 70% 1-RM load. Maximum isometric force, and rate of force development were determined using the isometric knee extension exercise on leg-extension machine interfaced with a force transducer. Performance data was collected at baseline (BL), after two weeks of normal training (Pre-OR), after OR phase (Post-OR), and after one week of recovery (POST). A 3x4 (group x time) repeated-measures ANOVA with Fisher LSD post-hoc was used to determine differences between groups and time. Significance was set at pRESULTS: There were no significant differences in knee extension variables (p>0.05). MF was higher in PL at Post-OR compared to BL and Pre-OR (2037 ± 626N vs. 1626±40N & 1581±92N; p-1 vs 78.7±11.3cm.s-1 & 75.3±6.7cm.s-1; p-1 vs 70.4±2.9cm.s-1 & 69.0±6.4cm.s-1; p0.05). CONCLUSION: Only dynamic RE (barbell squat) was sensitive to detect decreased performance compared to isometric RE (knee extension) in overreached subjects. Similarly, it appears power and velocity are more adversely affected by OR than measures of maximal force. Funding provided by Nutricia.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.026
GPT teacher head0.240
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2014
Admission routes1
Has abstractyes

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