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Record W2061511115 · doi:10.1139/h07-148

Nitric oxide and muscle blood flow in exercise

2008· review· en· W2061511115 on OpenAlexaffvenue
Michael E. Tschakovsky, Michael J. Joyner

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2008
Typereview
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsQueen's University
FundersNational Heart, Lung, and Blood Institute
KeywordsNitric oxideVasodilationBlood flowContext (archaeology)VasoconstrictionInternal medicineCardiologyMedicineBiology

Abstract

fetched live from OpenAlex

Despite being the subject of investigation for well over 100 years, the nature of exercising muscle blood flow control remains, in many respects, poorly understood. In this review we focus on the potential role of nitric oxide in vasodilation of muscle resistance vessels during a bout of exercise. Its contribution is explored in the context of whether it contributes to steady-state exercise hyperemia, the dynamic adjustment of muscle blood flow to exercise, or the modulation of sympathetic vasoconstriction in exercising muscle. It appears that the obligatory role of nitric oxide in all three of these categories is modest at best. The elucidation of the integrated nature of exercise hyperemia control in terms of synergy and redundancy of mechanism interaction remains in its infancy, and much more remains to be learned about the role of nitric oxide in this type of integrated 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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.017
GPT teacher head0.263
Teacher spread0.245 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations74
Published2008
Admission routes2
Has abstractyes

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