A New Method for Determining Prismatic Effects in Cylindrical Spectacle Corrections
Bibliographic record
Abstract
This study presents a new method of finding differential prismatic effects in an anisometropic spectacle correction containing cylindrical lenses. The calculations are based on dynamic spectacle magnifications rather than Prentice's rule. If an imaginary circular object is considered, cylindrical lenses will produce elliptical far point images, which can be superimposed on the spectacle plane for comparison. The difference between left and right ellipses, in any meridian, then represents the distance the eyes have to diverge in order to fuse the object of regard. This distance can be translated into prism diopters of differential prismatic effect. Although the conventional methods for finding this effect often result in very large errors, the new method can be performed with great accuracy. In part, this is because it uses the actual eccentricities of the two eyes rather than an assumed average eccentricity. Moreover, the method includes considerations of base curves and center thickness. Contrary to the classical methods, it can thus be applied to clinically realistic lenses.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".