Optical analysis of an accommodating intraocular lens
Bibliographic record
Abstract
PURPOSE: To model the feasibility of an accommodating intraocular lens (IOL) that allows near vision by means of an anterior translation within the capsular bag. SETTING: University of Waterloo, Waterloo, Ontario, Canada. METHODS: Model eyes were constructed and analyzed based on experimental data using Code V, a computerized optical design tool. The potential near vision of IOLs of different powers was calculated as they were moved anteriorly within the capsular bag. The conditions under which a spherical lens performs well and when an aspheric design should be considered were determined. RESULTS: Accommodation (the dioptric change from the far to the near point) varies linearly with lens movement and is sensitive to corneal and IOL powers. Simple equations were derived and accurately predicted induced accommodation. Retinal image quality varies significantly with pupil size and IOL power. However, image quality is minimally affected by the amount of induced accommodation. CONCLUSIONS: From an optical standpoint accommodation with adequate image quality can be achieved by anterior movement of a spherical IOL within the capsular bag.
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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 | 0.001 |
| 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".