New developments in the evolution of an efficient psychophysical test of spatial contrast sensitivity for pediatric patients
Bibliographic record
Abstract
Purpose: We have been attempting to develop an efficient psychophysical test of spatial contrast sensitivity (CS) for use with pediatric patients. To date, our CS card test (VSS, 2004) satisfies most of these requirements, except that it provides only rough estimates of CS threshold due to large step size and limited contrast range. Here we report on a new, more compact booklet version that addresses these limitations. Methods: The new test consists of (22 – 28 cm) sheets mounted in a spiral flip-binder. One half of each sheet contains a sine-wave grating of given spatial frequency (1.5, 3, 6, 12, or 24 cy/deg at 60 cm). For each SF set, contrast ranges from 3 to 160 CS units in 11 0.21 log CS steps. Testing is forced-choice and proceeds in modified staircase fashion. 150 preschoolers and 85 adults were tested with and without correction. Adults were also tested with the commercial Vistech CS chart. Results: Adult CSFs obtained with the CS booklet matched closely those obtained with the commercial CS test, both for corrected and uncorrected vision. Among children, those showing abnormal booklet CSFs also showed evidence of optical or ocular dysfunction. Conclusions: The CS booklet appears to be a significant improvement over previous psychophysical CS tests. It is very compact, easily portable, is tester and child-friendly, is relatively quick (about 4 min/eye), and appears sensitive to optical and visual pathology. An additional clinical advantage is its ability to estimate precise CS thresholds in children and adults with and without ocular pathology.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".