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Record W3178483276 · doi:10.1097/opx.0000000000001734

Athletes Demonstrate Superior Dynamic Visual Acuity

2021· article· en· W3178483276 on OpenAlexafffund
Alan Yee, Benjamin Thompson, Elizabeth L. Irving, Kristine Dalton

Bibliographic record

VenueOptometry and Vision Science · 2021
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsUniversity of Waterloo
FundersUniversity of Waterloo
KeywordsVisual acuityRepeated measures designEmmetropiaMedicineAthletesMonocularAnalysis of variancePost-hoc analysisAudiologyRefractive errorMathematicsOphthalmologyPhysical therapyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

SIGNIFICANCE: Athletes exhibit better dynamic visual acuity (DVA) compared with nonathletes, whereas action video game players (VGPs) perform more similarly to controls despite having similar static visual acuity and refractive errors. The differences in DVA between groups were not related to differences in static visual acuity, refractive error, or smooth pursuit gain. PURPOSE: The purpose of the study was to examine whether athletes and VGPs have superior DVA than controls (nonathletes, nongamers). METHODS: Forty-six participants (15 athletes, 11 VGPs, 20 controls) aged 21.7 years (standard deviation, 2.8 years) were recruited. Participants were emmetropic with equivalent monocular and binocular static visual acuity between groups. Dynamic visual acuity was assessed using predictable (horizontal) and unpredictable (random) motion targets at velocities of 5, 10, 20, and 30°/s. Smooth pursuit eye movements were assessed using a horizontal motion step-ramp stimulus at the same speeds. This study was pre-registered with the Center for Open Science (https://osf.io/eu7qc). RESULTS: At 30°/s, there were significant main effects of group (F = 4.762, P = .01) and motion type (F = 9.538, P = .004). Tukey post hoc analysis for groups indicated that athletes performed better than did the control group (t = -2.919, P < .02). An omnibus (group × motion type × speed) repeated measures ANOVA showed a main effect of speed (F = 110.137, P < .001) and a speed × motion-type interaction (F = 27.825, P < .001). Dynamic visual acuity decreased as speed increased, and the slope of the change was greater for random than for horizontal motion. Smooth pursuit gains were not significantly different between groups (P > .05). CONCLUSIONS: Athletes have superior dynamic visual acuity performance compared with controls at 30°/s. This between-group difference cannot be fully explained by differences in smooth pursuit eye movements and therefore may reflect other differences between the groups.

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)0.001
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 score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0150.001

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 head0.022
GPT teacher head0.479
Teacher spread0.457 · 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".

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Citations22
Published2021
Admission routes2
Has abstractyes

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