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Record W2129596086 · doi:10.4021/jnr.v3i1.171

Reversible Lower Motor Neuron Disease: A New Case of a Forgotten Disease

2013· article· en· W2129596086 on OpenAlexvenueno aff
Thiago Cardoso Vale, Denise da Silva Freitas, Luis Sergio Mageste, Leonardo Dornas de Oliveira, Antônio Lúcio Teixeira

Bibliographic record

VenueJournal of Neurology Research · 2013
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsnot available
Fundersnot available
KeywordsFasciculationMedicineLower motor neuronWeaknessTetraparesisMotor neurone diseaseMotor neuronUpper motor neuronDenervationProgressive muscular atrophyAtrophyDysphagiaDiseaseAmyotrophyPhysical medicine and rehabilitationAmyotrophic lateral sclerosisSurgeryAnesthesiaAnatomyInternal medicineRadiologyMagnetic resonance imaging

Abstract

fetched live from OpenAlex

Motor neuron disease (MND) is mostly associated with an irreversible course. Spontaneous recovery has been rarely reported. Herein described is a case of a spontaneous recovery of a lower motor neuron disease. A 38-year-old man complained of an insidious onset of weakness in the right upper limb that progressed to the lower limbs in 16 months. Physical examination revealed mild dysphonia, dysphagia, fasciculations, global hypotonia without prominent atrophy, proximal and distal tetraparesis. The patient was wheelchair-bound. EMG revealed signs of recent and chronic denervation involving bulbar, axial and appendicular myotomes with abundant pos itive sharp waves and fibrillations potentials in all muscles tested. In two year follow-up, the patient evolved with complete recovery and a new EMG study was completely normal. Reversible MND is a condition rarely reported, but physicians should keep in mind the possibility of its occurrence. doi: http://dx.doi.org/10.4021/jnr171w

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 score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.074
GPT teacher head0.375
Teacher spread0.301 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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