Comparison of the pupil card and pupillometer in measuring pupil size
Bibliographic record
Abstract
PURPOSE: To determine the difference in pupil size measured with the Colvard pupillometer in mesopic and scotopic luminance and with the Rosenbaum pupil card in mesopic luminance between 2 examiners. SETTING: Michel Pop Clinics, Montreal, Quebec, Canada. METHODS: Two examiners used the Colvard pupillometer and the Rosenbaum card to measure pupil size in 58 eyes. The Colvard pupillometer was used in mesopic and scotopic light conditions. The Rosenbaum card was used in mesopic luminance only. Pupil size was evaluated with a 1.0 mm interval scale at the nearest half millimeter. RESULTS: For the 3 sets of data, the limits of agreement and coefficient of interrater repeatability were calculated and a 2 x 2 factorial analysis of variance was performed. Because of interexaminer bias, measurements done in mesopic luminance with the Rosenbaum card were not statistically different from those with the Colvard pupillometer in scotopic luminance, although interrater repeatability of the Colvard pupillometer (0.8 mm) was superior to that of the Rosenbaum card (1.3 mm). CONCLUSIONS: Examiner bias was the greatest statistical bias in all sets of measures. Surgeons may want to opt for a "safe" limit of pupil size (ie, 0.5 to 0.8 mm greater than the measured size) when calculating optical zones in refractive surgery. Future devices for pupil measurement should be based on automatic adjustment sizing.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".