Resistance of Plastic Ophthalmic Lenses: The Effect of Base Curve on Different Materials During Static Load Testing
Bibliographic record
Abstract
PURPOSE: This study was designated to evaluate, through a static load test, the influence of lens base curve on the fracture resistance of three common plastic materials. METHODS: A JJ Lloyd load cell machine was used to test the fracture resistance of -4.00 D spherical lenses. The samples had a nominal center thickness of 2.0 mm and a base curve distributed in one of five groups (+0.50, +2.50, +4.50, +6.50, and +8.50 D). The lenses were manufactured in CR39, polycarbonate, and TL16, a high refractive index plastic (n = 1.599). RESULTS: The lens base curve influenced fracture resistance for all materials. For these materials, resistance increased as the base curve varied from +0.50 to +8.50 D. The resistance of CR39, TL16, and polycarbonate lenses was found to be linearly dependent on lens base curve. The effect is stronger for polycarbonate. Fracture resistance was higher for TL16 than for CR39, and polycarbonate was much more resistant to breakage than the two other materials. CONCLUSIONS: For a given power, the fracture resistance of an ophthalmic lens is reduced when its base curve has a low value. Consequently, the flattening of ophthalmic lenses for cosmetic purposes is not recommended as far as fracture resistance is concerned.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".