MétaCan
Menu
Back to cohort
Record W2131376616 · doi:10.2217/14796708.1.6.765

MRI findings in congenital muscular dystrophies associated with brain abnormalities

2006· article· en· W2131376616 on OpenAlexaff
Jiri Vajsar

Bibliographic record

VenueFuture Neurology · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsCongenital muscular dystrophyWhite matterMedicineMagnetic resonance imagingPathologyMuscular dystrophyLeukodystrophyRadiologyDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Magnetic resonance imaging (MRI) has become an important tool in diagnosing complex congenital muscular dystrophies (CMD) with brain abnormalities. Currently, there are two recognized types of CMDs with MRI brain abnormalities, firstly, laminin α2-chain-deficient CMD (MDC1A) with mutations in the LAMA2 gene, and secondly CMDs with hypoglycosylated α-dystroglycan which include Walker–Warburg syndrome (WWS), muscle–eye–brain disease (MEB), Fukuyama CMD (FCMD) and CMD types 1C and 1D (MDC1C and 1D). Brain MRI in MDC1A demonstrates abnormal white matter but rarely other brain abnormalities. In the latter group of CMDs, there is a whole spectrum of abnormalities involving both white and gray matter. The most severe MRI findings are in WWS. Patients with MEB, FCMD and MDC1C and lD also have gray and white matter abnormalities, which, in general, are less severe than those observed in WWS. There may be an overlap in these complex CMDs, both genotypically and in MRI findings.

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 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 score0.396
Threshold uncertainty score0.641

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 head0.002
GPT teacher head0.180
Teacher spread0.177 · 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 teacher head, 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

Citations1
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueFuture NeurologySame topicMuscle Physiology and DisordersFrench-language works237,207