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Record W1980061931 · doi:10.1002/mds.22776

Clinical measures of dysarthria in Friedreich Ataxia

2009· article· en· W1980061931 on OpenAlexfundno aff
Arunjot Singh, Elizabeth Epstein, Lauren Myers, Jennifer Farmer, David R. Lynch

Bibliographic record

VenueMovement Disorders · 2009
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsnot available
FundersNational Institutes of HealthMuscular Dystrophy AssociationCanadian Institutes of Health ResearchFriedreich's Ataxia Research Alliance
KeywordsDysarthriaAtaxiaIntelligibility (philosophy)AudiologyAphasiaPsychologyCerebellar ataxiaLanguage disorderPhysical medicine and rehabilitationMedicinePsychiatryCognition

Abstract

fetched live from OpenAlex

Dysarthria in Friedreich Ataxia (FA) is difficult to quantify. This study evaluated a series of performance measures for speech in 22 patients with genetically confirmed FA and 16 age-matched controls. Tests included the PATA examination, the PATAKA examination, the Oral Motor component of the Boston Aphasia examination, the Boston Cookie Theft description task, and the Assessment of Intelligibility of Dysarthric Speech. All measures, except the Cookie theft description task, demonstrated significantly lower scores for patients with FA when compared with controls and correlated with measures of disease progression. Thus, four of five measures capture speech dysfunction in FA and may provide feasible, inexpensive, quantitative testing for therapeutic monitoring in FA.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.565

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.058
GPT teacher head0.327
Teacher spread0.269 · 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 designBench or experimental
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

Citations17
Published2009
Admission routes1
Has abstractyes

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