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Record W2291625580 · doi:10.1136/jnnp-2015-312379.35

MOTOR NEURON DISEASE: A CASE OF MISGUIDED THERAPEUTIC NIHILISM

2015· article· en· W2291625580 on OpenAlexaff
Alexander M. Rossor, Dragana Josifova, Robin Howard, Alifa IsaacsItua

Bibliographic record

VenueJournal of Neurology Neurosurgery & Psychiatry · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA regulation and disease
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsWeaknessMedicineDysphagiaMissense mutationMotor neuronDiseasePediatricsSurgeryFacial weaknessSwallowingInternal medicineGeneticsGene

Abstract

fetched live from OpenAlex

We report the case of a 62 year old gentleman with sensorineuronal hearing loss beginning in the second decade. At the age of 40 he collapsed and was unable to walk more than a few metres. He was admitted to hospital and diagnosed with a motor neuron disease on the basis of an EMG. Examination at the time revealed bilateral deafness, facial weakness, dysphagia, dysphonia and both proximal and distal weakness. The family history was remarkable for two sisters who died of a similar condition in the second decade. In view of the combination of sensory neuronal deafness and a motor neuronopathy, a diagnosis of Brown Violetta Van Laera (BVVL) syndrome was made. A PEG tube was inserted and the patient was discharged to a nursing home for palliation. After several months, our patient discharged himself, reintroduced thickened fluids resulting in removal of the PEG tube. His clinical condition has continued to improve although he intermittently requires a wheelchair. Genetic testing of the SLC52A3 gene revealed two missense mutations (p.Glu36Lys and p.Val413Ala) confirming the clinical diagnosis of BVVL. SLC52A3 encodes a riboflavin transporter and in case series, riboflavin supplementation has halted or reversed the disease.

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 score0.246
Threshold uncertainty score0.808

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 head0.020
GPT teacher head0.273
Teacher spread0.253 · 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
Published2015
Admission routes1
Has abstractyes

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