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Effect of Aging on Stereoscopic Interocular Correlation

2006· article· en· W1975266168 on OpenAlexaff
Stéphane Laframboise, Danielle de Guise, Jocelyn Faubert

Bibliographic record

VenueOptometry and Vision Science · 2006
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsStereoscopic acuityStereoscopyStereopsisCorrelationOptometryAudiologyFixation (population genetics)MedicineStandard deviationVisual acuityPopulationOphthalmologyMathematicsComputer visionComputer scienceStatistics

Abstract

fetched live from OpenAlex

PURPOSE: This study was designed to evaluate the minimum interocular correlation (IOC) needed by the visual system to correctly perceive a static stereoscopic stimulus as a function of normal aging. It was also our goal to evaluate the feasibility of clinical charts testing this aspect of visual perception. METHODS: Stereoscopic IOC threshold was determined in 100 normal observers (average age +/- standard deviation, 45.7 +/- 20.4 years) drawn from a clinical population between the ages of 10 and 85. We used partially correlated red-green random dot stereograms (RDS) displaying flat, square surfaces at 360 arcsec of either crossed or uncrossed disparity. RESULTS: Older observers needed a higher binocular correlation to perceive the stereoscopic stimuli when compared with the younger groups. There is a slight increase in the threshold value of the individuals in the 45- to 64-year-old group and a further effect on the observers over 65 years of age. Data did not reveal any effects of gender, near point phoria, or fixation disparity on IOC thresholds. CONCLUSIONS: Normal aging produces a statistically significant deficit in binocular correlation processing. This process is marginally correlated with stereo acuity measures even when stereoacuity floor effects are factored out. Although further experiments directly comparing stereoacuity and IOC are necessary and more refining is required to obtain optimum parameters, clinical stereoscopic IOC test charts appear feasible and may not assess the same processes as stereoacuity charts.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.434
Teacher spread0.415 · 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 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

Citations18
Published2006
Admission routes1
Has abstractyes

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