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Record W2318442469 · doi:10.1002/mdc3.12355

Sweat Gland Denervation in Cerebellar Ataxia with Neuropathy and Vestibular Areflexia Syndrome (<scp>CANVAS</scp>)

2016· article· en· W2318442469 on OpenAlexfundno aff
Chizoba C. Umeh, Michael Polydefkis, Vinay Chaudhry, David S. Zee

Bibliographic record

VenueMovement Disorders Clinical Practice · 2016
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsnot available
FundersSun PharmaUniversity of TorontoUniversity of RochesterUniversity of OxfordJohns Hopkins UniversityAlnylam PharmaceuticalsBrigham and Women's Hospital
KeywordsSudomotorCerebellar ataxiaAtaxiaMedicineSweat glandVestibular systemPathologyAnatomyInternal medicineSWEATAudiology

Abstract

fetched live from OpenAlex

Cerebellar ataxia with neuropathy and vestibular areflexia syndrome (CANVAS) is a newly recognized disorder characterized by cerebellar ataxia, nonlength-dependent sensory impairment, and bilateral vestibular loss. Sudomotor dysfunction has been described in CANVAS; however, the underlying pathology is not well characterized. To describe novel histopathological features of this syndrome, 2 siblings are presented who had CANVAS with unique findings of sweat gland denervation. Skin biopsy testing was performed to assess sudomotor structure and revealed markedly reduced sweat gland nerve fiber density below the 2.5th percentile in both patients. These histopathological findings suggest that postganglionic sudomotor dysfunction is an additional feature of CANVAS.

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)0.001
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.316
Teacher spread0.280 · 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

Citations13
Published2016
Admission routes1
Has abstractyes

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