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Record W2024818041 · doi:10.1002/mus.1128

Depletion and sizes of motor units in spinal muscular atrophy

2001· article· en· W2024818041 on OpenAlexaff
Victoria Galea, Darcy Fehlings, Susan Kirsch, Alan J. McComas

Bibliographic record

VenueMuscle & Nerve · 2001
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsMcMaster University Medical CentreUniversity of TorontoMcMaster University
Fundersnot available
KeywordsSpinal muscular atrophySMA*Motor unitBicepsMedicineWeaknessAtrophyAnatomyBiceps brachii muscleElectromyographyPhysical medicine and rehabilitationCardiologyInternal medicineMathematics

Abstract

fetched live from OpenAlex

Motor unit number estimation (MUNE) was applied to the biceps brachii muscles of 13 young patients (age 5--24 years) with spinal muscular atrophy (SMA) and the results compared with those of healthy control subjects matched for age and gender. In the SMA patients, all motor unit (MU) estimates fell below the control range, and there was good correspondence between the values for the two arms in the same subject. No correlation could be found between the MUNEs and the severity of the weakness. This unexpected result was attributed to the presence of small and normal-sized MUs in the muscles of patients, in addition to MUs that appeared to be considerably enlarged. The threefold mean increase in MU potential size was insufficient to compensate for the MU loss. In addition, the study confirmed that there are, on average, approximately 130 MUs in the healthy biceps brachii muscle.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.029
GPT teacher head0.287
Teacher spread0.259 · 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

Citations56
Published2001
Admission routes1
Has abstractyes

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