Optical Coherence Tomography: An Introduction to the Technique and its Use
Bibliographic record
Abstract
This report describes the new optical imaging technique of optical coherence tomography (OCT). OCT is capable of high-resolution, micrometer-scale, cross-sectional imaging of biological tissue. The OCT for ophthalmic application uses 843-nm, near-infrared light, which produces a longitudinal resolution of 10 to 20 microm and a penetration depth of a few millimeters. The scans are displayed in a false color representation scale on which warm colors represent areas of high optical reflectivity and cool colors represent areas of minimal or no reflectivity. A cross-sectional view similar to a histology section is obtained. The cornea, iris, and lens may be visualized as well as the retina and optic nerve. OCT has been used to investigate several ocular diseases. These include macular disease, genetic retinal disease, retinal detachment and retinoschisis, choroidal tumors, optic nerve disorders, and glaucoma.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".