Qualitative Assessment of Scleral Shape Patterns Using a New Wide Field Ocular Surface Elevation Topographer
Bibliographic record
Abstract
Background and Objectives: Objective was to examine new findings regarding conjunctival/scleral shape mapped with a novel wide field elevation topography device and software, to propose a new classification system for scleral shape. Methods: The Scleral Shape Study Group (SSSG) collaborated on this research. Data was collected from 152 eyes of prospective scleral lens patients utilizing a new topography device and software specifically designed to measure and map the sclera out to as much as 22 mm. Circumferential scleral plots of sagittal height vs. meridian at 14, 15 and 16mm diameters from the corneal center were generated for each eye. Scleral shape patterns were reviewed in all cases and classified according to recurring characteristics. Results: Twelve eyes were excluded from the analysis due to incomplete data. Of the remaining 140 eyes, 8 (5.7%), of the plots were primarily spherical (Group 1) and 40 (28.6%) were primarily regularly toric, largely conforming to a toric (Sin2) curve with approximately 180° periodicity or interval between elevation to elevation or depression to depression (Group 2). Fifty-seven cases (40.7%) had asymmetric depressions (or steep areas) or asymmetric elevations (or flat areas) which were classified as Group 3. The remaining 35 cases (26%) had a recognizable toric pattern with elevations and depressions but they were irregularly spaced or did not have the customary 180° periodicity (Group 4). Conclusion: A new classification of conjunctival/scleral shape is presented based upon data now available through wide field elevation topography, which could be helpful in scleral lens fitting and potentially soft lens fitting as the landing zone of these lenses are beyond the corneal borders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".