Bibliographic record
Abstract
The fusional demand produced by anisometropic spectacles can be determined from the parameters of the lenses. This study compares several equations designed for this purpose. Two of the equations, recently described in other articles, contain small angle approximations and hence become less accurate for large angles of gaze eccentricity. Another two equations, introduced in this article, contain no approximations and can be used for accurate results at large gaze eccentricities. Results for all four equations are compared through a range of eccentricities of gaze and for various spectacle magnifications and typical examples of spectacle corrections. The conventional method of using Prentice's rule for finding interocular prismatic differences is also included in the comparisons. For eccentricities corresponding to the near visual point, the equations produce similar results, except Prentice's rule, which produces very large errors. Beyond the reading point eccentricity, results for the equations containing small angle approximations deviate significantly from each other and from the results obtained with the equations containing no approximations. It is recommended that the latter equations be used for large eccentricities.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".