MétaCan
Menu
Back to cohort
Record W2025620576 · doi:10.1177/08830738050200022101

Type I Spinal Muscular Atrophy Can Mimic Sensory-Motor Axonal Neuropathy

2005· article· en· W2025620576 on OpenAlexaff
Evdokia Anagnostou, Steven P. Miller, Marie‐Christine Guiot, George Karpati, Louise R. Simard, Marie-Emmanuelle Dilenge, Michael Shevell

Bibliographic record

VenueJournal of Child Neurology · 2005
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsMcGill UniversityMontreal Children's Hospital
Fundersnot available
KeywordsSpinal muscular atrophyMedicineAtrophyElectromyographyHereditary motor and sensory neuropathyPathologyMuscle atrophyAnatomyNeurosciencePhysical medicine and rehabilitationPsychologyDisease

Abstract

fetched live from OpenAlex

Spinal muscular atrophy is a group of allelic autosomal recessive disorders characterized by progressive motoneuron loss, symmetric weakness, and skeletal muscle atrophy. It is traditionally considered a pure lower motoneuron disorder, for which a current definitive diagnosis is now possible by molecular genetic testing. We report two newborns with a clinical phenotype consistent with that of spinal muscular atrophy type I and nerve conduction studies and electromyography suggesting more extensive sensory involvement than classically described with spinal muscular atrophy. Molecular testing confirmed spinal muscular atrophy in patient 1 but not in patient 2. Thus, in the setting of a suspected congenital axonal neuropathy, molecular testing might be necessary to distinguish spinal muscular atrophy type I from infantile polyneuropathy.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.280
Teacher spread0.265 · 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 designCase report
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

Citations31
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Child NeurologySame topicNeurogenetic and Muscular Disorders ResearchFrench-language works237,207