Bibliographic record
Abstract
PURPOSE: The 5-minute Schirmer test is a commonly described test for dry eye syndrome but is impractical for most ophthalmologists to perform routinely because of the 5-minute time frame. Hence, we decided to evaluate the intraindividual reliability of different wetting times of the Schirmer basal tear secretion test correlated to that of the standard 5-minute Schirmer test. METHODS: A prospective study was performed using 60 eyes of 30 patients. All patients had symptoms of dry eye syndrome. Patients were excluded if they had anatomic lid abnormalities that could interfere with the conduct of the test. The reliability of the Schirmer test at 30 seconds and 1, 2, 3, and 4 minutes was compared with that of the standard 5-minute test using the intraclass correlation coefficient (ICC). RESULTS: The ICC for each eye was only moderate at 30 seconds but was high to extremely high thereafter. Specifically, at 1 minute, the ICC for right eyes was 0.938 and for left eyes was 0.817. Furthermore, 100% of patients with severe dry eye (defined as a 5-minute Schirmer test of 5.5 mm or less) had a 1-minute Schirmer test less than or equal to 2 mm. Also, 80% of patients with a moderate dry eye (defined as a 5-minute Schirmer test between 5.5 to 10 mm) had a 1-minute test between 3 to 6 mm. CONCLUSION: Our results support the hypothesis that shorter durations of the 5-minute Schirmer test correlate highly with those of the 5-minute test. Specifically, the 1-minute test correlates highly with the 5-minute test and will make this test much more practical for ophthalmologists.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".