Ophthalmic lens effects in hartmann-shack measurements
Bibliographic record
Abstract
Hartmann-Shack methodology is well established for the measurement of the optical quality of the eye. Auxiliary lenses are used in situations where the aberrations of the eye-spectacle lens combination are of interest or to correct large refractive errors present in human subjects or induced in animal models of myopia. Measured aberrations are affected by auxiliary lenses through 1) the intrinsic aberrations of the lenses, 2) the vergence effect of the lenses and 3) the magnification effects of the lenses. Ray paths through spectacle and trial lenses can be approximated by paraxial optics and their higher-order aberrations are assumed to be small. The ocular optical aberrations for light incident from the spectacle focal point (the far point) will differ from those for light of zero vergence. The third effect of auxiliary lenses on aberrations is due to their magnification of the entrance pupil of the eye. The Hartmann-Shack device is designed to sample across the entrance pupil of the eye. The magnification of this pupil by the auxiliary lens in turn affects the samples taken. For instance, the entrance pupil of a spectaclely corrected myope will be minified by the correction onto the Hartmann-Shack array. If the pupil minification is not considered, these samples will be analyzed as if they originated from smaller pupil sizes and the amount of aberration intrinsic to the eye will be overestimated. Conversely, for the analysis of a fixed pupil size, the minification of the entrance pupil by the spectacle lens will increase the aberration of the spectacle/eye combination relative to the eye alone. The pupil minification differs from the spectacle minification. In a typical eye, with a −9D correction in place, entrance pupil minification was 12% and aberrations were overestimated by 20 %. We will describe two simple methods of dealing with this effect.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".