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Record W3164403907 · doi:10.1139/apnm-2021-0246

The influence of habitual breaks in sedentary time on cardiovagal baroreflex function

2021· article· en· W3164403907 on OpenAlexaffvenue
Myles W. O’Brien, Amera Al-Hinnawi, Yanlin Wu, Jennifer L. Petterson, Madeline E. Shivgulam, Jarrett A. Johns, Ryan J. Frayne, Derek S. Kimmerly

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2021
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsDalhousie University
Fundersnot available
KeywordsBaroreflexMedicineBlood pressureSedentary lifestyleSedentary behaviorAutonomic functionNoveltyCardiologyAutonomic nervous systemPhysical therapyInternal medicinePhysical medicine and rehabilitationHeart ratePhysical activityHeart rate variabilityPsychology

Abstract

fetched live from OpenAlex

Sedentary time has recently been included in the 24-h activity guidelines. However, the impact of habitual sedentary patterns on autonomic cardiovascular regulation are unclear. We tested the hypothesis that more sedentary time and fewer sedentary breaks were associated with lower cardiovagal baroreflex sensitivity. More frequent sedentary breaks, but not total sedentary time, was independently and positively associated with vagally mediated blood pressure control. Breaking up sedentary time could be more important than total sedentary time for cardiovascular health. Novelty: Breaks in sedentary time is an independent predictor of cardiovagal baroreflex sensitivity, with more frequent breaks associated with better vagally mediated blood pressure regulation.

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)0.002
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.006
GPT teacher head0.226
Teacher spread0.220 · 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

Citations18
Published2021
Admission routes2
Has abstractyes

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