Are the fluctuations in dynamic anterior surface aberrations of the human eye chaotic?
Bibliographic record
Abstract
The purpose of the study is to measure chaos in dynamic anterior surface aberrations and examine how it varies between the eyes of an individual. Noninvasive tear breakup time and dynamic corneal surface aberrations were measured for two open-eye intervals of 15 s. The maximal Lyapunov exponent (MLE) was calculated to test the nature of the fluctuations of the dynamic anterior surface aberrations. The average MLE for total higher-order aberration (HOA) was found to be small (+0.0102±0.0072) μm/s. No significant difference in MLE was found between the eyes for HOA (t-test; p=0.131). Data analysis was carried out for individual Zernike coefficients, including vertical prism as it gives a direct measure of the thickness of the tear film over time. The results show that the amount of chaos was small for each Zernike coefficient and not significantly correlated between the eyes.
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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 | 0.003 |
| 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".