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Record W2099266555 · doi:10.1139/h10-004

The John Sutton memorial lecture, 2009. Conductance systems: an integrative approach to the physiology of extreme conditions

2010· review· en· W2099266555 on OpenAlexaffvenue
Roy J. Shephard

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2010
Typereview
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCardiorespiratory fitnessLimitingVariety (cybernetics)Comparative physiologyVO2 maxOxygen transportSports medicineExercise physiologyAtmosphere (unit)OxygenPhysiologyBiochemical engineeringNeuroscienceCognitive scienceComputer scienceMedicinePsychologyChemistryHeart rateInternal medicineEngineeringBlood pressureArtificial intelligenceMechanical engineeringPhysical therapyThermodynamicsPhysics

Abstract

fetched live from OpenAlex

This presentation explores the value of mechanical, electrical, and mathematical analogues in understanding and evaluating a variety of closely integrated transport processes in human biology. Particular attention is directed to a major interest of John Sutton: the factors limiting transport of oxygen from the atmosphere to the working muscles when exercising in a variety of hostile environments. In most circumstances, the limiting term in a closely linked chain of conductances seems to be in the blood stream, and its magnitude can be estimated by measurements of maximal oxygen intake. Despite recent criticisms of this index by those who have proposed a feed-forward control of maximal aerobic effort, conductance theory suggests that the main limitation of oxygen transport is normally maximal cardiac output. Therefore, careful laboratory determinations of maximal oxygen intake continue to provide a convenient integrating assessment of an individual's cardiorespiratory function, with many important applications in sports medicine and exercise science.

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 score0.020
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0010.002
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0200.013

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 head0.301
Teacher spread0.268 · 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

Citations1
Published2010
Admission routes2
Has abstractyes

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