Accuracy and predictability of intraocular lens power calculation after laser in situ keratomileusis
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: To study the accuracy and predictability of intraocular lens (IOL) power calculation in eyes that had laser in situ keratomileusis (LASIK). SETTING: Gimbel Eye Centre, Calgary, Alberta, Canada. METHODS: Refractive outcomes in 6 cataract surgery and lensectomy eyes after previous LASIK were analyzed retrospectively. Target refractions based on measured and refraction-derived keratometric values were compared with postoperative achieved refractions. Differences between target refractions calculated using 5 IOL formulas and 2 A-constants and achieved refractions were also compared. RESULTS: The refractive error of IOL power calculation in postoperative LASIK eyes was significantly reduced when refraction-derived keratometric values were used for IOL power calculation. Persistent residual hyperopia still occurred in some cases; this was corrected by hyperopic LASIK. Refractive results appeared more accurate and predictable when the Holladay 2 or Binkhorst 2 formula was used for IOL power calculation. CONCLUSION: Hyperopic error after cataract surgery in post-LASIK eyes was significantly reduced by using refraction-derived keratometric values for IOL power calculation. Persistent hyperopic error was corrected by hyperopic LASIK.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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