Assessment of Variation in Bulbar Conjunctival Redness, Temperature, and Blood Flow
Bibliographic record
Abstract
PURPOSE: To assess the diurnal variation in bulbar conjunctival redness, conjunctival temperature, and conjunctival blood flow. METHODS: Bulbar redness was quantified by CIE u' chromaticity using a SpectraScan PR650 spectrophotometer. Conjunctival temperature was measured using a Tasco-Thi 500 infrared thermometer. Measurements of conjunctival blood flow were obtained using a modified Heidelberg Retinal Flowmeter (HRF). Measurements on 10 subjects were made on a periodic basis over the day and on waking. RESULTS: For each factor measured a cyclical pattern was observed, with highest values on waking, a reduction in values towards mid-day, and then a gradual increase over the remainder of the day. There was a significant effect of time for redness, temperature, and conjunctival blood flow (p < 0.001 for all three variables), with no significant difference in the cyclical pattern between eyes being observed (p = NS). CONCLUSIONS: Diurnal bulbar redness, temperature, and conjunctival blood flow variation may be objectively quantified and all three are lowest during the middle of the day and maximal at the start of the day. This information should be considered when undertaking studies in which redness, temperature, and ocular surface blood flow are important outcome variables and time of day is a potential confounding factor.
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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 | 0.001 |
| 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".