Measuring recognition visual acuity in young children – testability with the Waterloo Differential Acuity Test (WatDAT)
Bibliographic record
Abstract
CLINICAL RELEVANCE: Visual acuity measurement is important for the detection and monitoring of eye disorders. Developing accurate and sensitive visual acuity tests suitable for young children is therefore desirable. BACKGROUND: Recognition or form visual acuity (VA), which is measured with matching in children aged 3 years and up, is more sensitive for detecting visual deficits compared to resolution VA. The Waterloo Differential Acuity Test (WatDAT) is a proposed recognition VA test using the concept of identifying the "odd one out" among distractors. The WatDAT is expected to be cognitively easier than matching tests and therefore may be used in younger children. The purpose of this study is to investigate the testability of the WatDAT paradigm in children aged 12-36 months, and to determine the optimum format and number of distractors. METHODS: Fifty-one typically-developing children aged 12-36 months participated in the study. Data for Patti Pics (PP) and Face targets (FT) were collected for formats with 3, 4 and 5 distractors. The targets were presented binocularly on a computer touch screen at 30 cm. The task was to touch the face among identical non-faces or a house among circles. Following initial training, there were 5 presentations for each distractor format. Testability was defined as correctly identifying at least 4/5 presentations and was also determined for uncrowded PP symbols using matching. RESULTS: Of participants aged 18-36 months, 87% could perform the WatDAT PP targets with 3 distractors compared to 68% for the FT, while 48% could perform matching with PP. The testability for FT increased to 85% for children ≥22 months. Younger children showed lower testability. For the 3 distractor format, PP targets gave 9% testability in children 12 to <18 months, and FT gave a testability of 16% in children 12 to <22 months. CONCLUSION: WatDAT testability is higher than matching VA tests. This indicates that the newly developed WatDAT has potential for measuring recognition VA in children 18 months and older.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".