In vivo volumetric imaging of the human upper eyelid with ultrahigh-resolution optical coherence tomography
Bibliographic record
Abstract
The upper eyelid is a biological tissue with complex structure, essential for the maintenance of an optically clear ocular surface due to its physical (blinking) effect. The Meibomian glands (MGs) are structures that lie beneath the surface of the inner eyelid and are partially responsible for the production of the superficial oily layer of the tear film. The MGs are only superficially visible under magnification when the eyelid is everted. We present for the first time in vivo 3-D images of healthy and inflamed human MGs. Tomograms were acquired from the tarsal plate of everted human eyelids with a 1060-nm ultrahigh-resolution optical coherence tomography (UHOCT) system, with approximately 3 microm x 10 microm (axial x lateral) resolution in biological tissue at the rate of 91,911 A-scans/s. Comparison with histology shows that the UHOCT images reveal a spatial distribution of structures that appear to correspond with the MGs' acini and ducts (in healthy subjects), and accumulation of heterogeneous, highly scattering biological material and clear fluids in the visibly blocked glands. Noninvasive, volumetric high-resolution morphological imaging of the human tarsal area could have a significant impact in the clinical diagnosis of inflammatory and noninflammatory lid pathologies.
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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 | 0.001 |
| 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 | 0.001 | 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".