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Gain and Movement Time of Convergence‐Accommodation in Preschool Children

2004· article· en· W2037945650 on OpenAlexaff
Rajaraman Suryakumar, William R. Bobier

Bibliographic record

VenueOptometry and Vision Science · 2004
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsUniversity of WaterlooNatural Sciences and Engineering Research Council of Canada
Fundersnot available
KeywordsAccommodationConvergence (economics)Eye movementAge groupsPsychologyAudiologyMedicineOphthalmologyDemography

Abstract

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BACKGROUND: Convergence-accommodation is the synkinetic change in accommodation driven by vergence. A few studies have investigated the static and dynamic properties of this cross-link in adults but little is known about convergence-accommodation in children. The purpose of this study was to develop a technique for measuring convergence-accommodation and to study its dynamics (gain and movement time) in a sample of pre-school children. METHOD: Convergence-accommodation measures were examined on thiry-seven normal pre-school children (mean age = 4.0 +/- 1.31 yrs). Stimulus CA/C (sCA/C) ratios and movement time measures of convergence-accommodation were assessed using a photorefractor while subjects viewed a DOG target. Repeated measures were obtained on eight normal adults (mean age = 23 +/- 0.2 yrs). RESULTS: The mean sCA/C ratios and movement times were not significantly different between adults and children (0.10 D/Delta [0.61 D/M.A.], 743 +/- 70 ms and 0.11 D/Delta [0.50 D/M.A.], 787 +/- 216 ms). Repeated measures on adults showed a non-significant mean difference of 0.001 D/Delta. CONCLUSION: The results suggest that the possible differences in crystalline lens (plant) characteristics between children and adults do not appear to influence convergence-accommodation gain or duration.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.000

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 head0.015
GPT teacher head0.427
Teacher spread0.413 · 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

Citations13
Published2004
Admission routes1
Has abstractyes

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