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Regulation of Oxygen Consumption at the Onset of Exercise

2001· review· en· W2010882204 on OpenAlexaff
Richard L. Hughson, Michael E. Tschakovsky, Michael E. Houston

Bibliographic record

VenueExercise and Sport Sciences Reviews · 2001
Typereview
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsQueen's UniversityUniversity of Waterloo
Fundersnot available
KeywordsMetabolic control analysisOxygenConsumption (sociology)Aerobic exercisePhysical exerciseMetabolic rateMetabolic adaptationExercise physiologyVO2 maxPhysical therapyMetabolismMedicineInternal medicineChemistryHeart rate

Abstract

fetched live from OpenAlex

HUGHSON, R.L., M.E. TSCHAKOVSKY, and M.E. HOUSTON. Regulation of oxygen consumption at the onset of exercise. Exerc. Sport Sci. Rev., Vol. 29, No. 3, pp 129–133, 2001. Increased aerobic production of ATP at the onset of exercise could be limited by availability of metabolic substrates independent of O2, or interaction between O2 and metabolic substrates. We point out the importance of feedback control to match O2 supply to demand and discuss metabolic control at the onset of exercise.

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.075
GPT teacher head0.352
Teacher spread0.277 · 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

Citations156
Published2001
Admission routes1
Has abstractyes

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