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Record W2138673074 · doi:10.1139/h07-174

Determinants of<i>V</i>O<sub>2 max</sub>decline with aging: an integrated perspective

2008· review· en· W2138673074 on OpenAlexaffvenue
Andrew C. Betik, Russell T. Hepple

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2008
Typereview
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSkeletal muscleSarcopeniaSenescenceOxygen deliveryOxygenCardiac muscleVO2 maxInternal medicineChemistryHeart rateMedicine

Abstract

fetched live from OpenAlex

Aging is associated with a progressive decline in the capacity for physical activity. Central to this decline is a reduction in the maximal rate of oxygen utilization, or VO2 max. This critical perspective examines the roles played by the factors that determine the rate of muscle oxygen delivery versus those that determine the utilization of oxygen by muscle as a means of probing the reasons for VO2 max decline with aging. Reductions in muscle oxygen delivery, principally due to reduced cardiac output and perhaps also a maldistribution of cardiac output, appear to play the dominant role up until late middle age. On the other hand, there is a decline in skeletal muscle oxidative capacity with aging, due in part to mitochondrial dysfunction, which appears to play a particularly important role in extreme old age (senescence) where skeletal muscle VO2 max is observed to decline by approximately 50% even under conditions of similar oxygen delivery as young adult muscle. It is noteworthy that at least the structural aspects of the capillary bed do not appear to be reduced in a manner that would compromise the capacity for muscle oxygen diffusion even in senescence.

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)0.001
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.021
GPT teacher head0.299
Teacher spread0.278 · 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

Citations169
Published2008
Admission routes2
Has abstractyes

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