Utility of Light-Adapted Full-Field Electroretinogram ON and OFF Responses for Detecting Glaucomatous Functional Damage
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Bibliographic record
Abstract
Purpose: To compare parameters of electroretinogram (ERG) responses for their ability to detect functional loss in early stages of nonhuman primate (NHP) experimental glaucoma (EG), including photopic negative responses (PhNR) to a standard brief red flash on a blue background (R/B) and 200-ms-long R/B and white-on-white (W/W) flashes, to W/W flicker stimuli (5-50 Hz), and to a dark-adapted intensity series. Methods: Light-adapted ERGs were recorded in 12 anesthetized monkeys with unilateral EG. Amplitudes and implicit times of the a-wave, b-wave, and d-wave were measured, as well as amplitudes of PhNRs and oscillatory potentials for flash onset and offset. Flicker ERGs were measured using peak-trough and fundamental frequency analyses. Dark-adapted ERG parameters were modeled by Naka-Rushton relationships. Results: Only PhNR amplitudes were significantly reduced in EG eyes compared to fellow control (FC) eyes. The d-wave implicit time was delayed in EG versus FC eyes only for the W/W long flash, but in all eyes it was 10 to 20 ms slower for R/B versus the W/W condition. Flicker ERGs were <0.5 ms delayed in EG versus FC overall, but amplitudes were affected only at 5 Hz. The brief R/B PhNR amplitude had the highest sensitivity to detect EG and strongest correlation to parameters of structural damage. Conclusions: The PhNR to the standard brief R/B stimulus was best for detecting and following early-stage functional loss in NHP EG. Translational Relevance: These results suggest that there would be no benefit in using longer duration flashes to separate onset and offset responses for clinical management of glaucoma.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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