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Record W2025854047 · doi:10.1017/s0317167100006326

Bulbar Signs in Normal Population

2009· article· en· W2025854047 on OpenAlexvenueno aff
Kheng Seang Lim, Yin Cheng Hew, Hans Lau, T S Lim, Changhong Tan

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2009
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTonguePopulationYoung adultAudiologyPediatricsInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: There is lack of published data on bulbar signs among the healthy population. This study aims to determine the range of normality of bulbar signs particularly among the elderly. METHODS: Systemic examination of bulbar signs was carried out according to a predetermined protocol on a cohort of young and elderly healthy subjects. RESULTS: A total of 206 subjects were recruited in the study, 104 young adults with mean age of 20 years, and 102 elderly with mean age of 73 years. Uvula deviation was seen in 28 (26.9%) young subjects and 22 (21.6%) elderly. Irregular tongue border was seen in 17 subjects, unilateral in 4 subjects. Fourteen (6.8%) subjects had deviation on tongue protrusion. Occasional tremor of tongue on protrusion is common in both young and old. Persistent (severe) tongue tremor on protrusion was seen in 18.6% of the elderly, and 4.8% of the young. None of the subjects had tremor of tongue at rest. In gag reflex, absence of gagging response was common in elderly, seen in two thirds of the subjects on stimulation of the posterior pharyngeal wall. However, all the subjects had uvular movement. Habituation or suppression of gagging response was seen in close to 90% of young males. CONCLUSION: There is wide range of normality in bulbar signs in normal population, particularly among the elderly.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.030
GPT teacher head0.275
Teacher spread0.246 · 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.

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

Citations11
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicBotulinum Toxin and Related Neurological DisordersFrench-language works237,207