Effects of misalignment during corneal topography
Bibliographic record
Abstract
PURPOSE: To evaluate consequences of misalignment during corneal topography. SETTING: Maisonneuve-Rosemont Hospital, Montreal, Quebec, Canada. METHODS: Twenty-nine healthy subjects were enrolled in a study of 2 types of misalignment during Orbscan topography acquisition. The first was rotation, which was defined as angular deviation of the subject's visual axis away from the central fixation target, and the second was translation, defined as off-center displacement of the joined half slits on the computer screen during alignment by the technician. The effect of vertical and horizontal misalignments, by rotation or translation, was assessed. Study parameters included simulated keratometries (SimKs), mean corneal power (mean power), and corneal apex (R) and the asphericity factor (Q) values. Inferior-superior (I-S) and temporal-nasal (T-N) indices were calculated. Differences in parameter values between aligned and misaligned positions were studied. A mathematical model was also developed to simulate rotational and translational misalignment and consolidate clinical experimentation. RESULTS: The mean SimK values were slightly but significantly affected by rotation. The I-S value increased significantly with downward rotation and decreased with upward rotation of the eye, while T-N values increased significantly with temporal rotation and decreased with nasal rotation. The R and Q values increased with rotation. Overall, the topography parameters were minimally affected by translation. Comparable results were obtained with the theoretical model. CONCLUSIONS: Rotational misalignment of the eye during acquisition influenced topography more than the translational misalignment during focusing by the technician. Rotational misalignment induced corneal asymmetry on elevation and curvature maps as well as pseudokeratoconus patterns.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".