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Record W2892024399 · doi:10.1002/mus.26337

GNE myopathy in the bedouin population of Kuwait: Genetics, prevalence, and clinical description

2018· article· en· W2892024399 on OpenAlexaff
Hadil Alrohaif, Oksana Pogoryelova, Abdullah Al‐Ajmi, Lulwa A. Aljeryan, Nuwayer H. Alrashidi, Sara A. Alefasi, Andoni Urtizberea, Hanns Lochmüller, Lailá Bastaki

Bibliographic record

VenueMuscle & Nerve · 2018
Typearticle
Languageen
FieldMedicine
TopicInflammatory Myopathies and Dermatomyositis
Canadian institutionsOttawa HospitalChildren's Hospital of Eastern OntarioUniversity of Ottawa
FundersSeventh Framework Programme
KeywordsMyopathyWastingMedicineMutationPopulationAge of onsetDiseasePediatricsGeneticsInternal medicineGeneBiology

Abstract

fetched live from OpenAlex

INTRODUCTION: GNE myopathy is a rare recessive myopathy caused by mutations in the GNE gene. It is mainly a distal myopathy with relative sparing of the quadriceps muscle. METHODS: Patients with distal myopathies from Kuwait were examined and tested for the Middle Eastern GNE gene founder mutation, p.M743T. Patients were further studied for disease-associated features. RESULTS: GNE myopathy was confirmed in 14 of the 37 patients (37.8%) screened. All cases were caused by the p.M743T mutation. Age of onset and time from disease onset to loss of ambulation were variable. Both wasted and hypertrophied calf muscles were noted. Severely affected quadriceps were present in 1 patient, and ptosis, ophthalmoplegia, and tongue wasting in another. DISCUSSION: The scope of the p.M743T mutation now includes the Arabian Peninsula. Variations in age of onset, disease progression, and distribution in patients harboring the same mutation suggest the role of other genetic- and environment-modifying factors. Muscle Nerve 58: 700-707, 2018.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.028
GPT teacher head0.305
Teacher spread0.277 · 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

Citations14
Published2018
Admission routes1
Has abstractyes

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