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NIRS-derived skeletal muscle oxidative capacity is correlated with aerobic fitness and independent of sex

2020· article· en· W3044376357 on OpenAlexafffund
Austin T. Beever, Thomas R. Tripp, Jenny Zhang, Martin J. MacInnis

Bibliographic record

VenueJournal of Applied Physiology · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAerobic capacitySkeletal muscleRespiratory compensationOxidative phosphorylationVO2 maxInternal medicineGastrocnemius muscleRespiratory exchange ratioLactate thresholdEndocrinologyVastus lateralis muscleChemistryAnaerobic exerciseBiologyMedicineHeart rateBiochemistryPhysical therapyBlood lactateBlood pressure

Abstract

fetched live from OpenAlex

Near-infrared spectroscopy (NIRS) can be used to measure skeletal muscle oxidative capacity. Here, we demonstrated that NIRS-derived skeletal muscle oxidative capacity of the vastus lateralis was independent of sex, reliable across and within days, and correlated with maximal and submaximal indices of aerobic fitness, including maximal oxygen uptake, lactate threshold, and respiratory compensation point. These findings highlight the utility of NIRS for investigating skeletal muscle oxidative capacity in females and males.

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)0.001
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.220
Teacher spread0.206 · 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

Citations68
Published2020
Admission routes2
Has abstractyes

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