MétaCan
Menu
Back to cohort
Record W1592823251 · doi:10.1002/ana.24194

Hypomyelinating leukodystrophies: Translational research progress and prospects

2014· review· en· W1592823251 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.

Bibliographic record

VenueAnnals of Neurology · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA regulation and disease
Canadian institutionsMcGill UniversityMontreal Children's Hospital
FundersBiotechnology and Biological Sciences Research CouncilNational Institutes of HealthEuropean CommissionWellcome Trust
KeywordsLeukodystrophyClinical trialTranslational researchNeuroscienceMagnetic resonance imagingMedicineDiseaseIntensive care medicineBioinformaticsPathologyPsychologyBiologyRadiology

Abstract

fetched live from OpenAlex

Hypomyelinating leukodystrophies represent a genetically heterogeneous but clinically overlapping group of heritable disorders. Current management approaches in the care of the patient with a hypomyelinating leukodystrophy include use of serial magnetic resonance imaging (MRI) to establish and monitor hypomyelination, molecular diagnostics to determine a specific etiology, and equally importantly, careful attention to neurologic complications over time. Emerging research in oligodendrocyte biology and neuroradiology with bedside applications may result in the possibility of clinical trials in the near term, yet there are significant gaps in knowledge in disease classification, characterization, and outcome measures in this group of disorders. Here we review the biological background of myelination, the clinical and genetic variability in hypomyelinating leukodystrophies, and the insights that can be obtained from current MRI techniques. In addition, we discuss ongoing research approaches to define potential outcome markers for future clinical trials.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.697

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.141
GPT teacher head0.439
Teacher spread0.298 · 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