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Record W2134917201 · doi:10.1139/cjpp-2014-0042

Heart rate at 4 s after the onset of exercise in endurance-trained men

2014· article· en· W2134917201 on OpenAlexvenueno aff
Divanei Zaniqueli, Elis Aguiar Morra, Eduardo Miranda Dantas, Marcelo Perim Baldo, Luciana Carletti, Anselmo José Perez, Sérgio Lamêgo Rodrigues, José Geraldo Mill

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2014
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsHeart rateMedicineInternal medicineCardiologyAerobic exerciseHeart rate variabilityEndurance trainingEndocrinologyBlood pressure

Abstract

fetched live from OpenAlex

It has been suggested that the increase in heart rate (HR) at the onset of exercise is caused by vagal withdrawal. In fact, endurance runners show a lower HR in maximum aerobic tests. However, it is still unknown whether endurance runners have a lower HR at 4 s after the onset of exercise (4th-sec-HR). We sought to measure the HR at the onset of the 4 s exercise test (4-sET), clarifying its relationship to heart rate variability (HRV), spectral indices, and cardiac vagal index (CVI) in endurance runners (ER) and healthy untrained controls (CON). HR at 4th-sec-HR, CVI, and percent HR increase during exercise were analyzed in the 4-sET. High frequency spectrum (HF-nu), low frequency spectrum (LF-nu), and low frequency/high frequency band ratio (LF/HF) were analyzed from the HRV. ER showed a significantly higher HF, and both a lower LF and LF/HF ratio compared with the CON. ER presented a significantly lower 4th-sec-HR, although neither CVI nor HR increases during exercise were statistically different from the CON. In conclusion, ER presented a lower 4th-sec-HR secondary to increased vagal influence over the sinus node. CVI seems to be too weak to use for discriminating individuals with respect to the magnitude of HR vagal control.

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 categoriesInsufficient payload (model declined to judge)
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 score0.934
Threshold uncertainty score0.999

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)0.0020.000

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 head0.009
GPT teacher head0.257
Teacher spread0.248 · 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.

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

Citations7
Published2014
Admission routes1
Has abstractyes

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