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Record W3126487631 · doi:10.5935/0004-2749.20210026

Visual outcomes of audio-luminous biofeedback training for a child with idiopathic nystagmus

2021· letter· en· W3126487631 on OpenAlexaff
Monica Daibert-Nido, Yulia Pyatova, Michelle Markowitz, Samuel N. Markowitz

Bibliographic record

VenueArquivos Brasileiros de Oftalmologia · 2021
Typeletter
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineAudiologyAudio visualNystagmusBiofeedbackTraining (meteorology)Physical medicine and rehabilitationComputer scienceMultimediaPhysics

Abstract

fetched live from OpenAlex

Microperimetry biofeedback training is a vision rehabilitation method that involves the training of attention and oculomotor control, and the rehabilitation of poorly located and non-functional preferred retinal loci. It can significantly improve distance and near visual acuity in age-related macular degeneration. Previous studies have shown that biofeedback training using electrical nystagmography can reduce nystagmus amplitude and increase foveation time. However, these improvements have not been sustained following training sessions. We hereby report a pediatric case of idiopathic nystagmus in an 11-year old patient treated with microperimetric biofeedback to improve visual acuity and fixation stability. The training had a beneficial impact, positively affecting fixation stability as well as distance and near reading vision. Subjectively, improvement in quality of life was also reported. Conversely to previous studies, the positive effects in this case were maintained for as long as twelve months following therapy. To the best of our knowledge, this is the first case with long-term benefits to be reported in the literature.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.053
GPT teacher head0.289
Teacher spread0.236 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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