Validity and Repeatability of a Novel Dynamic Visual Acuity System
Bibliographic record
Abstract
PURPOSE: In many sports, athletes rely on visual information from the environment to perform. Some literature suggests athletes have superior visual abilities to non-athletes, particularly on tasks representative of the visual demands of their sport, such as dynamic acuity, eye movement accuracy and speed, and peripheral vision. Other literature suggests there is no difference between athletes and non-athletes, at least when standard clinical assessments are employed. A limitation of the literature is that almost none of the research has been conducted with standardized, validated tools. This is partly caused by a lack of readily available tools to measure tasks representative of the visual demands of sport, and available tests have typically not been validated against current clinical standards. The purpose of this study is to examine the validity and repeatability of a novel visual acuity system (moV&; V&MP Vision Suite) recently developed in the Vision & Motor Performance Lab (V&MP). moV& permits the measurement of many visual function parameters including dynamic visual acuity with predictable, random, and jittering target motion. METHODS: Twenty-five participants attended two study visits, separated by a minimum of 2 weeks. At each visit, static and dynamic visual acuity was measured using Snellen, ETDRS, and moV& charts. Static visual acuities were compared to determine the validity of moV&, and both static and dynamic visual acuities were compared between visits to determine the test-retest repeatability. RESULTS: moV& static visual acuities are clinically similar to visual acuities measured with the ETDRS chart (moV&, -0.09 ± 0.13; ETDRS, -0.03 ± 0.11, concordance correlation coefficient 0.726). Additionally, all static, dynamic, and jitter visual acuities demonstrate good test-retest repeatability (Lin's concordance correlation coefficient range 0.451-0.953). CONCLUSIONS: moV& provides good clinical measures of static visual acuity that are comparable to both Snellen and ETDRS measures. Dynamic visual acuity measures demonstrate good test-retest repeatability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".