Comparison of Optic Disc Margin Identified by Color Disc Photography and High-Speed Ultrahigh-Resolution Optical Coherence Tomography
Bibliographic record
Abstract
OBJECTIVE: To determine the correspondence between optic disc margins evaluated using disc photography (DP) and optical coherence tomography (OCT). METHODS: From May 1, 2005, through November 10, 2005, 17 healthy volunteers (17 eyes) had raster scans (180 frames, 501 samplings per frame) centered on the optic disc taken with stereo-optic DP and high-speed ultrahigh-resolution OCT (hsUHR-OCT). Two image outputs were derived from the hsUHR-OCT data set: an en face hsUHR-OCT fundus image and a set of 180 frames of cross-sectional images. Three ophthalmologists independently and in a masked, randomized fashion marked the disc margin on the DP, hsUHR-OCT fundus, and cross-sectional images using custom software. Disc size (area and horizontal and vertical diameters) and location of the geometric disc center were compared among the 3 types of images. RESULTS: The hsUHR-OCT fundus image definition showed a significantly smaller disc size than the DP definition (P <.001, mixed-effects analysis). The hsUHR-OCT cross-sectional image definition showed a significantly larger disc size than the DP definition (P <.001). The geometric disc center location was similar among the 3 types of images except for the y-coordinate, which was significantly smaller in the hsUHR-OCT fundus images than in the DP images. CONCLUSION: The optic disc margin as defined by hsUHR-OCT was significantly different than the margin defined by DP.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| 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".