Recent advances and future directions on the use of optical coherence tomography in neuro-ophthalmology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Optical coherence tomography (OCT) is a noninvasive imaging technique used to qualitatively and quantitatively analyze various layers of the retina. OCT of the retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL) is particularly useful in neuro-ophthalmology for the evaluation of patients with optic neuropathies and retrochiasmal visual pathway disorders. OCT allows for an objective quantification of edema and atrophy of the RNFL and GCIPL, which may be evident before obvious clinical signs and visual dysfunction develop. Enhanced depth imaging OCT allows for visualization of deep structures of the optic nerve and has emerged as the gold standard for the detection of optic disc drusen. In the evaluation of compressive optic neuropathies, OCT RNFL and GCIPL thicknesses have been established as the most important visual prognostic factor. There is increasing evidence that inclusion of OCT as part of the diagnostic criteria for multiple sclerosis (MS) increases its sensitivity. Moreover, OCT of the RNFL and GCIPL may be helpful in the early detection and monitoring the treatment of conditions such as MS and Alzheimer's disease. OCT is an important aspect of the neuro-ophthalmologic assessment and its use is likely to increase moving forward.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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