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Record W3006589714 · doi:10.1113/ep088187

Central cardiovascular system limits to aerobic capacity

2020· article· en· W3006589714 on OpenAlexafffund

Bibliographic record

VenueExperimental Physiology · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of Waterloo
FundersNational Heart, Lung, and Blood InstituteNatural Sciences and Engineering Research Council of CanadaNational Institutes of Health
KeywordsAerobic capacityPaceCompetitor analysisVariable (mathematics)Event (particle physics)Aerobic exerciseExercise physiologyEnergy metabolism

Abstract

fetched live from OpenAlex

New Findings What is the topic of this review? The limits to maximal aerobic capacity. What advances does it highlight? A synthesis of data and ideas about what limits maximal aerobic capacity demonstrates the central roles of cardiac output, stroke volume and red blood cell mass in the complex physiological responses to maximal exercise. In healthy humans these factors, along with skeletal muscle blood flow, dominate systemic delivery of oxygen to the contracting muscles and set the upper limit of aerobic energy production by skeletal muscles. In elite athletes and patients with pulmonary disease the lungs can also limit oxygen uptake and delivery. Abstract In this paper we review the physiological determinants of and discuss the role this variable plays as a determinant of endurance exercise performance. Because the ability to sustain a given pace during a competitive athletic event requires competitors to ‘manage’ fatigue and go as fast as possible without fatiguing prematurely, is one of the variables that sets the physiological upper limit for sustained energy production by the contracting skeletal muscles.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.033
GPT teacher head0.246
Teacher spread0.214 · 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

Citations30
Published2020
Admission routes2
Has abstractyes

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