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Record W4353015922 · doi:10.1080/2576117x.2023.2188836

Vision Beyond Vision: Lessons Learned from Amblyopia

2023· article· en· W4353015922 on OpenAlexafffund
Agnes Wong

Bibliographic record

VenueJournal of Binocular Vision and Ocular Motility · 2023
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersCanada Foundation for InnovationJohn and Melinda Thompson Endowment Fund in Vision NeurosciencesCanadian Institutes of Health ResearchPrevent BlindnessBrandan’s Eye Research Foundation
KeywordsFixation (population genetics)Saccadic maskingPerceptionEye movementPsychologyVisual acuitySmooth pursuitAdaptation (eye)Binocular visionStereopsisAudiologyVisual perceptionComputer visionComputer scienceMedicineNeuroscienceOphthalmology

Abstract

fetched live from OpenAlex

Amblyopia is characterized by spatiotemporal uncertainty in the visual system. In addition to its effects on vision, amblyopia also exerts a widespread impact on other systems. Many of these changes are observed not only during amblyopic eye viewing but also during fellow eye and binocular viewing. They generally correlate with the severity of visual acuity and stereo acuity loss. The affected systems include: (1) oculomotor control manifested as abnormal fixation, saccades, smooth pursuit, and saccadic adaptation; (2) motor control with altered programming, execution, and temporal dynamics of eye-hand coordination, and decreased ability of the sensorimotor system to adapt to changes in the visual environment; (3) balance control with decreased postural stability; (4) multisensory integration characterized by reduced McGurk effect and altered cross-modal interactions in audiovisual perception; and (5) auditory localization manifested as impaired spatial hearing as a result of abnormal developmental calibration of the auditory map. To detect amblyopia early, a targeted approach is required to identify children from low-income families through in-school visual screening, supplemented by follow-up care and free eyeglasses in high-needs schools.

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)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.004
Open science0.0010.002
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.098
GPT teacher head0.390
Teacher spread0.293 · 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
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

Citations6
Published2023
Admission routes2
Has abstractyes

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