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Record W2325804641 · doi:10.1139/apnm-2013-0214

Physiological and metabolic responses as function of the mechanical load in resistance exercise

2013· article· en· W2325804641 on OpenAlexvenueno aff
Sebastian Buitrago, Nicolas Wirtz, Ulrich Flenker, Heinz Kleinöder

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2013
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsnot available
Fundersnot available
KeywordsConcentricIsometric exerciseEccentricResistance trainingWork (physics)ChemistryMathematicsMedicineInternal medicinePhysicsGeometryThermodynamics

Abstract

fetched live from OpenAlex

The present study aimed to investigate the relationship between the mechanical load during resistance exercise and the elicited physiological responses. Ten resistance-trained healthy male subjects performed 1 set of resistance exercise each at 55%, 70%, and 85% of 1 repetition maximum for as many repetitions as possible and in 4 training modes: 4-1-4-1 (4 s concentric, 1 s isometric, 4 s eccentric, and 1 s isometric successive actions), 2-1-2-1, 1-1-1-1, and explosive (maximum velocity concentric). Mean concentric power and total concentric work were determined. Oxygen uptake (V̇O2) was measured during exercise and for 30 min post exercise. Total volume of consumed oxygen (O2 consumed) and excess post-exercise oxygen consumption (EPOC) were calculated. Maximum blood lactate concentration (LAmax) was also determined. V̇O2 exhibited a linear dependency on mean concentric power. Mean concentric power did not have a detectable effect on EPOC and LAmax. An augmentation of total concentric work resulted in significant linear increase of O2 consumed and EPOC. Total concentric work caused a significant increase in LAmax. In general, a higher mechanical load induced a larger physiological response. An increase in mean concentric power elicited higher aerobic energy turnover rates. However, a higher extent of total concentric work augments total energy cost covered by oxidative and (or) glycolytic pathways.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.929
Threshold uncertainty score0.502

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.236
Teacher spread0.224 · 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

Citations16
Published2013
Admission routes1
Has abstractyes

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