Why what you have been taught about the optic disc may not be entirely true
Bibliographic record
Abstract
Abstract Clinicians evaluate neuroretinal rim health according to the appearance of the optic disc, the clinically visible surface of the optic nerve head (ONH). Recent anatomic findings with optical coherence tomography challenge the basis and accuracy of current rim evaluation for 3 reasons: (1) The DM is rarely a single anatomical structure or an identifiable junction, such as the inner edge of border tissue. In most eyes it corresponds variably to multiple anatomical structures. (2) In some regions of all ONHs, Bruch’s membrane extends internally beyond the DM (towards the centre of the ONH) and is both clinically and photographically invisible. Since in these areas the outer border of the rim is the termination of Bruch’s membrane and not the more external DM, the rim is narrower than that with clinical or photographic evaluation. (3) Because current rim width measurements are made in a fixed plane without reference to the orientation of the rim tissue, for the same number of axons, the rim width will be greater in cases where the orientation of the rim tissue is more horizontal (for example in the temporal sector of tilted optic discs) compared to when it is more perpendicular. This presentation will review and interpret ONH anatomy detected with optical coherence tomography pertaining to optic disc examination and demonstrate why a paradigm change for clinical assessment of the optic nerve head is now necessary.
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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 | 0.007 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.019 |
| Insufficient payload (model declined to judge) | 0.017 | 0.010 |
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".