Thickness Mapping of the Cornea and Epithelium Using Optical Coherence Tomography
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
PURPOSE: To measure corneal and epithelial thickness across four meridians using Optical Coherence Tomography (OCT) and to compare these measurements between normal non-lens wearers (NLW), rigid gas permeable (RGP) lens wearers, and RGP-wearing keratoconics (KC). METHODS: Both eyes of 60 subjects were measured (20 NLW, nine female:11 male, 27.6 +/- 5.9 years; 20 RGP, 20 female, 23.9 +/- 7.6 years; and 20 KC, seven female:13 male, 32.4 +/- 8.1 years). A customized fixation target employing LEDs in eight directions of gaze was attached to the OCT and corneal images obtained. Raw OCT scans were analyzed to yield values for corneal and epithelial thickness and color-coded maps were compiled. RESULTS: Central corneal thickness (CCT) was thinnest in KC (447 +/- 68 microm) and similar between RGP (518 +/- 32 microm; pKC < 0.001) and NLW (517 +/- 21 microm) (p(KC) < 0.001 NLW pRGP > 0.05). Peripheral corneal thickness in NLW was thickest in the superior temporal and thinnest in the inferior (I) regions (superior temporal(thickest) vs. I(thinnest) p < 0.001). Central epithelial thickness was thinnest in KC (44 +/- 7 microm), followed by RGP (50 +/- 4 microm), then NLW (54 +/- 2 microm) (pKC < 0.001 NLW p(RGP) < 0.05). Central epithelial thickness in the KC group was significantly thinner than in the RGP group (p < 0.001). In the NLW group, peripheral epithelial thickness was thicker (63 +/- 5 microm) than central (p < 0.001) and was thickest in the superior (S) region and thinnest in the inferior (I) region (S(thickest) vs. I(thinnest) p < 0.001). KC epithelium was thinnest in the inferior temporal meridian (42 +/- 5 microm). CONCLUSIONS: Thickness of the normal cornea and epithelium was greatest in the superior region. In all groups, the inferior cornea and epithelium was thinnest, and to a greater extent in the KC group.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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