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Record W2612195624 · doi:10.1002/mus.25394

Motor unit number estimation and neuromuscular fidelity in 3 stages of sarcopenia

2016· article· en· W2612195624 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMuscle & Nerve · 2016
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSarcopeniaMotor unitPhysical medicine and rehabilitationMedicineAnkleElectromyographyInternal medicinePhysical therapyPsychologyAnatomy

Abstract

fetched live from OpenAlex

INTRODUCTION: Loss of motor units (MUs) and alterations in MU properties are major factors in development of sarcopenia. The purpose of this study was to compare MU properties among 3 groups categorized as either pre-sarcopenic (n = 7), sarcopenic (n = 7), or severely sarcopenic (n = 5), all with similarly aged subjects (75-82 years). METHODS: Using decomposition-enhanced quantitative electromyography, MU number estimates and neuromuscular stability measures of near-fiber (NF) jitter and jiggle were derived in addition to contractile properties of ankle dorsiflexors. RESULTS: MU number estimates were similar across groups; however, maximal voluntary strength in the severe sarcopenia group was 27% and 37% less than the sarcopenic and pre-sarcopenic groups, respectively. Moreover, NF jiggle was 31% greater in the severe group compared with pre-sarcopenia, NF jitter was 43% greater in the severe group compared with the pre-sarcopenic group. CONCLUSION: Unlike MU number estimates, strength and MU stability differed across groups and related to degree of sarcopenia. Muscle Nerve 55: 676-684, 2017.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.281
Threshold uncertainty score0.320

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.040
GPT teacher head0.335
Teacher spread0.296 · 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