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Record W4224863250 · doi:10.1177/00084174221088417

Participation and Functional Independence in Adults With Recessive Spastic Ataxia of Charlevoix-Saguenay

2022· article· en· W4224863250 on OpenAlexfundvenueaboutno aff
Samar Muslemani, Isabelle Lessard, Caroline Lavoie, Isabelle Côté, Bernard Brais, Jean Mathieu, Cynthia Gagnon

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2022
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsnot available
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchMuscular Dystrophy Canada
KeywordsPhysical medicine and rehabilitationSpasticBalance (ability)PsychologySeclusionPhysical therapyMedicineCerebral palsyPsychiatry

Abstract

fetched live from OpenAlex

Background. Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is a progressive disorder where upper and lower extremities motor performances may bring participation restriction. Purpose. To document participation in adults with ARSAC and explore associations with motor performances. Method. Twenty-eight participants took part in the study. Participation was assessed using the LIFE-H. Motor performance was assessed using several outcomes including the SARA, LEMOCOT, Berg Balance Scale, 10-Meter Walk Test, and Finger-to-nose Test. Findings. Participation was significantly lower in the wheelchair user subgroup. Also, for 29 activities out of 77, at least 15% of participants reported severely disrupted participation. Participation was correlated with upper and lower limbs coordination, walking ability, balance, disease severity, and fine dexterity (Spearman r = .41–0.85, p < .03). Implications. Results showed significant participation restrictions and suggest that interventions aiming to improve or compensate upper and lower limbs functions could help to decrease disease burden.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.953
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.086
GPT teacher head0.312
Teacher spread0.226 · 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 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

Citations2
Published2022
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Occupational TherapySame topicGenetic Neurodegenerative DiseasesFrench-language works237,207