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Interrupting prolonged sitting with repeated chair stands or short walks reduces postprandial insulinemia in healthy adults

2020· article· en· W3101771394 on OpenAlexafffund
Jenna B. Gillen, Stephanie Estafanos, Eric Williamson, Nathan Hodson, Julia M. Malowany, Dinesh Kumbhare, Daniel R. Moore

Bibliographic record

VenueJournal of Applied Physiology · 2020
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsToronto Rehabilitation InstituteUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaMitacsCanadian Institutes of Health ResearchCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaACSM Foundation
KeywordsPostprandialSquatSittingInsulinMedicineArea under the curveMealInternal medicineSquatting positionEndocrinologyAnimal sciencePhysical therapyBiology

Abstract

fetched live from OpenAlex

Breaking up prolonged sitting with intermittent walking breaks can improve glycemic control. Here, we demonstrated that interrupting prolonged sitting every 30 min with 1 min of repeated chair stands was as effective as 2-min treadmill walks for lowering postprandial insulinemia in healthy adults. Markers of contraction- and insulin-mediated muscle glucose uptake were unchanged. Repeated chair stands as a form of body-weight resistance activity may represent a cost- and space-efficient activity break for mitigating cardiometabolic-disease risk.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.316
Teacher spread0.276 · 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 designNon-randomized trial
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

Citations28
Published2020
Admission routes2
Has abstractyes

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