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Record W2157867155 · doi:10.1159/000331319

Cerebellar Cognitive Affective Syndrome and Autosomal Recessive Spastic Ataxia of Charlevoix-Saguenay: A Report of Two Male Sibs

2012· article· en· W2157867155 on OpenAlexaboutno aff
W.M.A. Verhoeven, J.I.M. Egger, Amir I.M. Ahmed, Berry Kremer, Sascha Vermeer, Bart P.C. van de Warrenburg

Bibliographic record

VenuePsychopathology · 2012
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyDisinhibitionCerebellumCerebellar vermisNeuroscienceAtaxiaCognitionCerebellar ataxiaCerebellar DegenerationCognitive deficitCognitive impairment

Abstract

fetched live from OpenAlex

BACKGROUND: Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is a rare neurodegenerative disorder caused by mutations in the SACS gene (13q12) encoding the protein sacsin. It is characterized by early-onset cerebellar ataxia, lower limb spasticity, sensorimotor axonal polyneuropathy, and atrophy of the superior cerebellar vermis. Cerebellar disorders in general may be accompanied by the cerebellar cognitive affective syndrome (CCAS) which presents with disturbances of executive functioning, spatial cognition, linguistic capacities, and affect. SAMPLING AND METHODS: Two middle-aged brothers with ARSACS, one of whom was referred for behavioral disinhibition, are described. A detailed neuropsychiatric and neuropsychological assessment was performed. RESULTS: Apart from motor symptoms, motivational deficits along with cognitive and behavioral dysfunctions were present; these were much more pronounced in the older sib. CONCLUSIONS: These observations add to the literature which suggests that the cerebellum, apart from its significance for motor behavior, plays a functional role in human cognition and affect. The nonmotor symptoms of ARSACS are discussed in terms of the CCAS.

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)0.003
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.025
GPT teacher head0.303
Teacher spread0.278 · 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

Citations30
Published2012
Admission routes1
Has abstractyes

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