Exploring new strategies to record and analyse clinical electroretinograms
Bibliographic record
Abstract
Abstract Purpose Investigate if the combination of time‐frequency domain analysis and ERG dipole rotation reveals hidden features of the normal ERG that could be instrumental in the interpretation of nearly extinguished ERG responses. Methods Analyses were conducted on photopic ERGs (Photopic Hills: PH) obtained from normal subjects (n=75) and patients (n=65) affected with various retinopathies. A Discrete Wavelet Transform (DWT) was done on each ERGs and key descriptors (Holder exponent and wavelet coefficient maxima) were calculated. Dipole rotation was obtained by combining 11 gaze positions (0, 8, 16, 24, 32 and 40 degrees nasal or temporal to center) with 4 electrode locations [corneal (CE), lower lid (LL), external (EC) and internal canthi (IC)]. Results The Holder exponent follows a parabola, while some of the local wavelet maxima seem to follow a PH‐like like distribution (b‐wave and OPs) or a logistic growth function (a‐wave). In still recordable pathological ERGs, the wavelet maxima matched that found in normal ERGs evoked at low stimulus intensities while in nearly extinguished ERGs (<10% of normal) the wavelet coefficients were significantly lower. Irrespective of the direction of gaze, there was little variation in DTL ERGs. EC ERGs were the only ones to reverse in polarity (seen 5 degrees nasal to fixation in nasal to temporal shift). Conclusion The parameters obtained with the DWT offers useful and reproducible tools to help identify subtle features of residual ERGs and therefore should allow for a more accurate quantification of low‐voltage ERGs responses. Finally, our results suggest that varying the gaze and electrode positions would represent a valuable addition to the recording of clinical ERGs. Funded by NSERC.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".