In vivo volumetric imaging of the human corneo-scleral limbus with spectral domain OCT
Bibliographic record
Abstract
The limbus is the structurally rich transitional region of tissue between the cornea on one side, and the sclera and conjunctiva on the other. This zone, among other things, contains nerves passing to the cornea, blood and lymph vasculature for oxygen and nutrient delivery and for waste, CO(2) removal and drainage of the aqueous humour. In addition, the limbus contains stem cells responsible for the existence and healing of the corneal epithelium. Here we present 3D images of the healthy human limbus, acquired in vivo with a spectral domain optical coherence tomography system operating at 1060nm. Cross-sectional and volumetric images were acquired from temporal and nasal locations in the human limbus with ~3µm x 18µm (axial x lateral) resolution in biological tissue at the rate of 92,000 A-scans/s. The imaging enabled detailed mapping of the corneo-scleral tissue morphology, and visualization of structural details such as the Vogt palisades, the blood and lymph vasculature including the Schlemm's canal and the trabecular meshwork, as well as corneal nerve fiber bundles. Non-invasive, volumetric, high resolution imaging reveals fine details of the normal human limbal structure, and promises to provide invaluable information about its changes in health and disease as well as during and after corneal surgery.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".