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Record W3135179755 · doi:10.1017/cjn.2021.41

Dystonia in Performing Artists: Beyond Focal Hand Dystonia

2021· review· en· W3135179755 on OpenAlexvenueno aff
Somdattaa Ray, Pramod Kumar Pal

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2021
Typereview
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsDystoniaFocal dystoniaPhysical medicine and rehabilitationTask (project management)PsychologyMedicineNeuroscienceAudiology

Abstract

fetched live from OpenAlex

Overuse of specific muscles in perfecting movements in performing arts makes an artist prone to many medical conditions. Musicians' hand dystonia is focal task-specific dystonia (FTSD) of hand among musicians that has been extensively studied. However, embouchure, lower limbs, and laryngeal muscles can also be affected among musicians. Embouchure dystonia (ED) refers to dystonia of the perioral and facial muscles that occurs in musicians while playing embouchure instruments. It is essential to identify ED since the dystonia might become persistent and non-task-specific if the musician continues to play the instrument. Task-specific dystonia of lower limbs among musicians has been exclusively reported among drummers. The diagnosis rests on electromyogram (EMG) of the involved muscles during the task. Singer's dystonia (SD) refers to task-specific laryngeal dystonia that occurs only while singing. The diagnosis of SD is based on laryngeal EMG and spectrographic analysis. Cortical hyperexcitability, loss of inhibition, and aberrant plasticity are central to the pathogenesis in both ED and musicians' hand dystonia. The pathophysiological studies in SD are limited. This review aims to discuss the lesser known dystonias among performing artists - ED, FTSD of lower limb, and SD.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.646
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.004
Science and technology studies0.0030.011
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.006
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 head0.050
GPT teacher head0.318
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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreReview

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

Citations12
Published2021
Admission routes1
Has abstractyes

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