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How does Bangerter filter affect the normal visual perception?

2011· article· en· W2001576187 on OpenAlexaff
Jinghua Li, Ziqiang Ding, Daming Deng, Y.Y. Chan, Tricia Benjamin, X Chen, RF Hess, Yu Meng

Bibliographic record

VenueActa Ophthalmologica · 2011
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsVisual acuityContrast (vision)PsychologyAudiologyOphthalmologyOptometryMedicineOpticsPhysics

Abstract

fetched live from OpenAlex

Abstract Purpose The Bangerter filter (BF) has become an alternate form of amblyopia patching treatment due to its high social‐psychological compliance and effective therapeutic outcomes. This study aims to investigate the effects of different BF densities on the normal visual system in order to quantify filter densities based on vision perception variables. Methods Thirty‐two binocularly normal subjects participated in this study. Visual acuity (VA), vernier acuity (VNA) and contrast sensitivity (CS) under spatial frequencies (SF) of 0.5, 1, 2, 5, 10 cyl/deg were measured while the dominant eye was patched with randomly selected BF of densities: 0.8, 0.6, 0.4, 0.2. Results Mean VA and VNA values under the four BF densities were a) 0.29, 0.30, 0.35, 0.54 logMAR and b) 3.24, 4.81, 5.29, 8.19 min of arc respectively. There was a significant difference (p<0.05) in VA change between BF 0.2 and rest of the density groups. BF 0.8 and 0.2 groups showed a significant VNA change compared to BF 0.6 and 0.4 (p<0.05). There were no significant effects noted in CS at SF of 0.5, 1 and 2 cyl/deg across low to high BF groups (p>0.05). BF 0.2 was the only density that had a significant influence on middle and high SF (5 and 10 cyl/deg) (p<0.05). Conclusion BF does not alter vision perception abilities in a predictable manner suggested by the manufacturer. Only the high BF density has shown a significant change. Careful attention must be paid on the inconsistencies in low and middle BF densities for the patching treatment.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.062
GPT teacher head0.335
Teacher spread0.273 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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