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Record W2910083364 · doi:10.1159/000490285

Advances in Vestibular Rehabilitation

2019· review· en· W2910083364 on OpenAlexaff
Shaleen Sulway, Susan L. Whitney

Bibliographic record

VenueAdvances in oto-rhino-laryngology · 2019
Typereview
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsToronto General HospitalUniversity Health Network
Fundersnot available
KeywordsVestibular rehabilitationVestibular systemPhysical medicine and rehabilitationOscillopsiaContext (archaeology)VertigoRehabilitationMedicineBalance (ability)Vestibular disordersVestibulePsychologyAudiologyPhysical therapySurgery

Abstract

fetched live from OpenAlex

Vestibular rehabilitation is an exercise-based program that has been in existence for over 70 years. A growing body of evidence supports the use of vestibular rehabilitation in patients with vestibular disorders, and evolving research has led to more efficacious interventions. Through central compensation, vestibular rehabilitation is able to improve symptoms of imbalance, falls, fear of falling, oscillopsia, dizziness, vertigo, motion sensitivity and secondary symptoms such as nausea and anxiety. Early intervention is advised for falls prevention and symptom management; however, symptomatic patients with chronic vestibular disorders may still demonstrate benefit from a course of vestibular rehabilitation. Recent advances in balance and gait training, gaze stability training, habituation training, use of virtual reality, biofeedback, and vestibular prostheses are discussed in this chapter in the context of unilateral and bilateral vestibular disorders.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.003

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 head0.028
GPT teacher head0.359
Teacher spread0.332 · 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 designNot applicable
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

Citations112
Published2019
Admission routes1
Has abstractyes

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