Distribution of Overnight Corneal Swelling Across Subjects With 4 Different Silicone Hydrogel Lenses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: To determine distribution of central corneal swelling (CCS) across subjects after 8 hr of sleep in eyes wearing silicone hydrogel lenses with various oxygen transmissibility (Dk/t) values and in eyes without lenses. METHODS: Twenty-nine neophytes wore lotrafilcon A (Dk, 140), balafilcon A (Dk, 91), galyfilcon A (Dk, 60), and senofilcon A (Dk, 103) lenses in powers -3.00, -10.00, and +6.00 diopters on separate nights, in random order, and on 1 eye only. The contralateral eye (no lens) served as the control. Central corneal thickness was measured using a digital optical pachometer before lens insertion and immediately after lens removal on waking. RESULTS: The average difference between the mean (7%) and the median (6.8%) CCS of all lenses was only 0.2%, suggesting a normal distribution. There was no correlation between the mean and the range of the CCS (r=0.058, P=0.766). Normal CCS distributions were also found with each lens-wearing eye and the control eye (P>0.20 for all). There was a significant correlation between lens-wearing eye and control eye (r=0.895, P<0.001) and between lotrafilcon A and each of the other 3 lenses for mean CCS across the study participants (P<0.001 for all). CONCLUSIONS: Distribution of corneal swelling in both lens-wearing eye and control eye followed a normal curve. An individual's corneal swelling response seems to be independent of lens type.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it