Influence of Vision on Ocular Comfort Ratings
Bibliographic record
Abstract
PURPOSE: To evaluate the influence of blur on ocular comfort while systematically manipulating vision using habitual refractive correction, induced spatial blur, dioptric defocus, and under the absence of visual structure. METHODS: Twenty emmetropic subjects rated vision, ocular comfort, and other sensations (burning, itching, and warmth) under clear viewing condition, spatial blur, and dioptric defocus, each lasting for 5 min. During each condition, subjects viewed digital targets projected from a distance of 3 m, and vision and ocular sensations were rated using magnitude estimation. Dioptric defocus was induced using +6.00DS contact lens, and equivalent spatial blur was produced by spatially filtering the targets. In a separate study, 15 participants rated vision and comfort while viewing a ganzfeld and behind an occluding patch (each of which provided an absence of visual structure) in addition to the above experimental conditions. Repeated-measures analysis of variance was used to compare the ratings of vision and comfort under the different experimental conditions. RESULTS: Vision under blurred conditions (both spatial blur and dioptric defocus) was rated significantly different (p < 0.001) from clear viewing condition. Vision was significantly different when targets were dioptrically defocused than when they were spatially blurred (p < 0.001). Ratings of comfort showed significant differences between clear and blurred conditions (p < 0.001). However, there was no significant difference in comfort ratings between dioptric defocus and spatial blur (p value at least 0.28). There were also no differences in comfort (p value at least 0.99) between clear vision, ganzfeld viewing, and occlusion despite the lack of visual structure in the latter two conditions. CONCLUSIONS: There does seem to be an association between clarity of vision and ocular comfort. Although the pathways for ocular surface pain and vision are perhaps exclusive, complex psychological influences such as nocebo or Hawthorne effects can subtly influence the participants to anticipate a change in comfort when vision is blurred.
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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 | 0.002 |
| 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) | 0.002 | 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".