Diurnal Variation of Corneal Sensitivity and Thickness
Bibliographic record
Abstract
PURPOSE: To measure the diurnal variation of central corneal sensitivity and thickness over 24 hours. METHODS: A noncontact pneumatic esthesiometer to measure central corneal sensitivity and an optical pachymeter to measure central corneal thickness were used on 20 noncontact lens wearers. These measurements were performed at 22:00 before 8 hours of sleep and on the following day on eye opening and at hourly intervals between 7:00 and 22:00. RESULTS: Central corneal sensitivity varied by 35% over the 24 hours. Sensitivity was significantly lower by 17.1 +/- 2.1% on eye opening and recovered to the level of the previous night after 4 hours. Corneal sensitivity continued to increase throughout the day but was not significantly higher. Central corneal thickness varied by 3.9% over the 24 hours. The mean overnight corneal swelling was 2.9 +/- 0.31%, and 2 hours after eye opening, the cornea had deswelled to the same thickness as the previous night. The cornea thinned further throughout the day, but there were no statistically significant differences between the values after 14:00. There was a high correlation between corneal sensitivity and thickness over time (r = 0.8; p < 0.05). DISCUSSION: Corneal sensitivity correlated with corneal thickness: both were higher on awakening and then decreased and remained below the levels measured the previous night. This may be due to physiological and/or environmental factors. The lack of significant differences between the values after 14:00 suggests that baseline may be measured at any time from 7 hours after eye opening.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".