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Record W1965069951 · doi:10.1139/h01-007

Functional and Metabolic Consequences of Sarcopenia

2001· review· en· W1965069951 on OpenAlexaff
Anthony A. Vandervoort, T. Brock Symons

Bibliographic record

VenueCanadian Journal of Applied Physiology · 2001
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsWestern University
Fundersnot available
KeywordsSarcopeniaIsometric exercisePhysical medicine and rehabilitationMuscle hypertrophyEccentricMedicineStimulus (psychology)MyosinPhysical therapyPsychologyCardiologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Sarcopenia associated with the normal aging process is often combined with the detrimental effects of a sedentary lifestyle in older adults, leading to a significant reduction in reserve capacity of the neuromuscular system. A clear example of the aging effect is the pattern of reduction in muscle strength after the sixth decade for both isometric and concentric contractions. However, older adults are relatively stronger for movements in which muscles lengthen, due to the inherent advantage of eccentric contractions, plus their stiffer muscle structures and prolonged myosin cross-bridge cycles. Also, the capacity for physiological adaptations in the motor pathways remains into very old age when an appropriate exercise stimulus is given, and older adults can obtain adaptations in both enhanced neural control of motor units and increased protein synthesis leading to moderate muscle hypertrophy. Since periods of sedentary lifestyle or bed rest due to illness can have severe detraining consequences on the neuromuscular function of an older person, long-term prevention strategies are advocated to avoid excessive physical impairments and activity restrictions in this age group.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.027
GPT teacher head0.258
Teacher spread0.232 · 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

Citations328
Published2001
Admission routes1
Has abstractyes

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