A Comparison of Three Different Scales for Rating Contact Lens Handling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: To compare the validity, responsiveness, and reliability of three subjective rating scales applied to soft contact lens (SCL) handling. METHODS: Fifty-four adapted SCL wearers handled three different types of lenses on two occasions and rated the handling with each scale: visual analogue scales (VAS), 20-interval visual analogue scales with descriptors (VAD) and Likert rating scales with five intervals (LRS). RESULTS: There were significant differences between the scales (p < 0.01) and between the subjective ratings of lens handling (p < 0.001). VAS showed the least variability, exhibited the highest construct validity, were the most responsive, and were the most reliable: interclass correlations (0.63), coefficient of repeatability (27.5), and correlation between test and retest (Spearman r = 0.65, [all p < 0.05]). Higher repeatability, because of the fewer intervals of LRS, was not demonstrated and, generally, LRS was the least satisfactory scale. Handling was rated as easiest using VAD and most difficult using LRS. CONCLUSIONS: Although all three scales can be used to provide measures of lens handling, VAS may provide a simple and repeatable tool for measuring subjective responses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.000 | 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 it