Die Form der Sklera und ihre Korrelation mit topografischen Parametern der Hornhaut
Bibliographic record
Abstract
Purpose. This review paper aims to summarize the outcomes of the different studies investigating the correlation between corneal and scleral profiles, outline the relationship between corneal and scleral curvatures and asymmetry, and describe the correlation between corneal astigmatism and scleral toricity in regular and irregular corneas. Material and Methods. Literature was reviewed from PubMed. A total of 48 articles were specifically selected for the current study. Results. The scleral and corneal radii are directly correlated; the greater the corneal radius, the larger the scleral radius. The cornea and sclera become gradually flatter and asym- metric as the distance from the corneal optical line increases. Similar to the central cornea, the limbal area is more likely to be spherical. The horizontal asymmetry between the nasal and temporal areas is greater than the vertical asymmetry, with the nasal region of the ocular surface being the flattest. In eyes with keratoconus, the sclera is steeper, more asym- metric, and irregular. Cone decentration predicts asymmetric sclera. Corneal and scleral toricity are more likely correlated when corneal astigmatism is greater than 2.00 D. Conclusion. Some correlations were found between corneal and scleral topography; however, performing both corneal and scleral topography are necessary when fitting contact lenses. Further investigation is needed with larger groups matched in age, refractive error, and biometry and comparing smaller or steepest eyes (i.e., Asiatic population) with larger or flatter eyes. It would also be interesting to compare such correlations in primary and secondary ectasia, investigating whether the scleral shape changes in secondary ectasia. Keywords Corneal topography, scleral profile, ocular surface asymmetry, profilometry, ocular surface radii, contact lens fitting
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".