Minimizing Pupil Size Dependence in Flicker ERG Using Stiles–Crawford Compensation
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Bibliographic record
Abstract
Purpose: This study determined the impact of the Stiles-Crawford effect (SCE) on electroretinograms (ERGs). Compensating for the SCE can improve the diagnostic reliability of ERGs by providing a stimulus minimally affected by pupil size. Methods: Flicker ERGs were recorded from 10 healthy subjects at 3-minute intervals over 21 minutes after mydriasis. The RETeval system adjusted retinal illuminance in real time based on pupil size measurements, using a Troland stimulus and preset SCE compensation factors (ρdevice) of 0, 0.05, 0.085, and 0.12 mm-2. Results: Larger pupil areas led to prolonged implicit times with ρdevice = 0 and 0.05 mm-2, whereas ρdevice = 0.12 mm-2 reduced implicit time. Amplitudes were lower with ρdevice = 0 mm-2 but increased with ρdevice = 0.085 and 0.12 mm-2. The values that minimized pupil size dependence were ρdevice = 0.086 mm-2 for the implicit time of the fundamental component of the ERG and ρdevice = 0.05 mm-2 for all other measures. Variability in ERGs based on pupil size is predicted to be ≤7% of the associated 95% reference interval for Troland stimuli over the range of nonmydriatic pupil sizes, compared to ≤43% for luminance stimuli over the range of mydriatic pupil sizes. Conclusions: Using Troland stimuli with ρdevice = 0.05 mm-2 for all cone-mediated ERGs would minimize the impact of pupil size, although the improvement would be modest for ERGs performed with Troland stimulation without SCE compensation on non-dilated subjects. Translational Relevance: Applying the appropriate SCE coefficient (ρdevice) enables more reliable ERG measurements, improving diagnostic accuracy despite pupil size variations in clinical settings.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it