MétaCan
Menu
Back to cohort

EXERCISE AND HYPOXIC EFFECTS ON FATIGUE MANIFESTATIONS IN HUMAN SKELETAL MUSCLE

2001· article· en· W2018187910 on OpenAlexaffabout
D. J. Barr, Todd A. Duhamel, Jonathon R. Fowles, Laura R. McCabe, S Sandiford, Jonathan D. Schertzer, H Green

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHigh Altitude and Hypoxia
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsIsometric exerciseHypoxia (environmental)MedicineCardiologyStimulationInternal medicineMuscle fatigueContraction (grammar)Physical medicine and rehabilitationPhysical therapyAnesthesiaElectromyographyChemistryOxygen

Abstract

fetched live from OpenAlex

To determine the role of exercise, as modified by hypoxia, on fatigue development and recovery, 8 untrained volunteers (age = 20.1 ± 0.66 yr; x ± SE) performed knee extension isometric exercise for 60 min followed by 30 min of recovery during both normoxia (N) and hypoxia (H; FI 02 = 0.14). The exercise was performed at 50% of maximal voluntary contraction (MVC) and 50% duty cycle (5 s contraction and 5 s recovery). Fatigue was assessed both by changes in MVC and at different frequencies of transclutaneous electrical stimulation. Repetitive activity resulted in both a time dependent loss of MVC and 100 Hz torque. For 10 Hz, an initial increase in torque was observed at 5 min of exercise followed by progressive decreases. No further changes in force were observed during the recovery period regardless of the property assessed. During H both MVC and 100 Hz torque were persistently lower than H regardless of time. E = exercise; R = recovery These results demonstrate that hypoxia impairs force production but only at high force outputs, an effect that occurs prior to exercise and which persists throughout exercise and recovery. Supported by NSERC (Canada)Table

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.013
GPT teacher head0.284
Teacher spread0.271 · 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 designBench or experimental
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

Citations0
Published2001
Admission routes2
Has abstractyes

Explore more

Same venueMedicine & Science in Sports & ExerciseSame topicHigh Altitude and HypoxiaFrench-language works237,207