Schirmer tear test‐1 with open or closed eyelids: An evaluation in brachycephalic and nonbrachycephalic dogs
Bibliographic record
Abstract
PURPOSE: Assess aqueous tear production when measured with the dogs' eyelids open or closed. METHODS: Thirty healthy dogs (15 Shih Tzus, 15 Labrador retrievers) were recruited. With the order of testing randomized for each dog, two sessions (separated by 30 min) of STT-1 testing were performed with the dogs' eyelids closed or open. Schirmer strip wetness (every 10 s for 60 s) and number of time(s) the strip dislodged during testing were recorded in each eye. Preferred STT-1 method was surveyed via a global Listserv of the veterinary ophthalmology community. RESULTS: STT-1 values were significantly higher in closed versus open eyes in Shih Tzus (18.6 ± 2.7 mm/min vs. 16.3 ± 2.5 mm/min; p = .002) and Labrador retrievers (21.6 ± 2.9 mm/min vs. 17.8 ± 3.2 mm/min, p < .001), findings that were also significant at times <60 s for either breed (p ≤ .004). Schirmer strips dislodged from six dogs with open eyelids and no dogs with closed eyelids. Maximal STT-1 difference with closed versus open eyelids was 13 mm/min in Labrador retrievers and 7 mm/min in Shih Tzus. Survey results from 275 veterinarians showed STT-1 performed with "closed eyelids" (38.5%), "open eyelids" (26.9%), or "never paid attention, sometimes closed, sometimes open" (34.6%). CONCLUSIONS: Eyelids status (closed or open) during STT-1 testing had a significant impact on aqueous tear secretion in brachycephalic and nonbrachycephalic dogs, highlighting the importance of consistency when repeating STT-1 in a canine patient. STT-1 differences are likely due to sustained reflex tearing throughout the test duration when the dogs' eyelids are closed.
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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 | 0.000 |
| 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 | 0.001 |
| 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 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".