The Effect of Laser in situ Keratomileusis on Low Contrast Vision
Bibliographic record
Abstract
PURPOSE: To determine the effects of laser in situ keratomileusis (LASIK) on low contrast visual acuity. METHODS: Thirty eyes of 15 LASIK patients with myopia and astigmatism were evaluated preoperatively, and 1 and 3 months postoperatively. High contrast visual acuity (HCVA), low contrast visual acuity (LCVA), and contrast threshold were determined. RESULTS: Mean spherical correction (SE) was -3.24 +/- 1.90 D; 16 eyes had a mean SE between -1.00 and -3.00 D, and 14 eyes were between -3.25 and -6.50 D. There was no significant change in HCVA observed at 1 and 3 months in any eye. There was a decrease in LCVA in eyes with a correction >3 D SE at 1 month (P=.04), which returned to normal at 3 months (P=.13). There was an increase in the contrast threshold at 1 month (P=.016). When eyes were divided into groups, those with >3D SE correction had an increase in contrast threshold at 1 month (P=.002); no change was seen in eyes with <3D SE correction (P=.15). At 3 months, contrast threshold was similar to baseline values in all eyes (P=.226). CONCLUSION: LASIK transiently decreased low contrast visual function in patients with greater than 3.00 D of myopic correction.
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 | 0.000 | 0.001 |
| 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".