OCT-Detected Optic Nerve Head Neural Canal Direction, Obliqueness, and Minimum Cross-Sectional Area in Healthy Eyes
Bibliographic record
Abstract
Purpose To assess anterior scleral canal opening (ASCO) offset relative to Bruch's membrane opening (BMO) (ASCO/BMO offset) so as to determine neural canal direction, obliqueness, and minimum cross-sectional area (NCMCA) in 362 healthy eyes. Design Cross-sectional study. Methods After optical coherence tomography optic nerve head and retinal nerve fiber layer thickness (RNFLT) imaging, BMO and ASCO were manually segmented. Planes, centroids, size, and shape were calculated. Neural canal direction was defined by projecting the neural canal axis vector (connecting BMO and ASCO centroids) onto the BMO plane. Neural canal obliqueness was defined by the angle between the neural canal axis and the BMO plane perpendicular vector. NCMCA was defined by projecting BMO and ASCO points onto a neural canal axis perpendicular plane and measuring the area of overlap. The angular distance between superior and inferior peak RNFLT was measured, and correlations between RFNLT, BMO, ASCO, ASCO/BMO offset, and NCMCA were assessed. Results Mean (SD) NCMCA was significantly smaller than either the BMO or ASCO area (1.33 (0.42), 1.82 (0.38), 2.22 (0.43) mm 2 , respectively), and most closely correlated to RNFLT ( P < .001, R 2 = 0.158). Neural canal direction was most commonly superior-nasal (55%). Mean neural canal obliqueness was 39.4° (17.3°). The angular distance between superior and inferior peak RNFLT correlated to neural canal direction ( P ≤ .008, R 2 = 0.093). Conclusions ASCO/BMO offset underlies neural canal direction, obliqueness, and NCMCA. RNFLT is more strongly correlated to NCMCA than to BMO or ASCO, and its peripapillary distribution is influenced by neural canal direction.
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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) | 0.001 | 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 | 0.001 |
| 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 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".