Ocular diagnostics, ophthalmic findings, and conjunctival microbiome in the Chilean flamingo (<i>Phoenicopterus chilensis</i>)
Bibliographic record
Abstract
OBJECTIVE: To establish normative data for selected ocular diagnostic tests and commensal conjunctival microflora and describe the incidence of ocular pathology in Chilean flamingos. ANIMALS STUDIED: A total of 41 Chilean flamingos were examined at the Blank Park Zoo in Des Moines, Iowa. PROCEDURES: In 20 flamingos, blink rate was assessed undisturbed in their exhibit, then gentle manual restraint was used to assess palpebral fissure length (PFL), aqueous tear production (phenol red thread test [PRTT] in one eye, endodontic absorbent paper point tear test [EAPPTT] in the other), intraocular pressure (IOP; rebound tonometry), and fluorescein staining. Twenty-one other flamingos were brought to a darkened area for neuro-ophthalmic examination, slit lamp biomicroscopy, and indirect ophthalmoscopy. Swabs from seven flamingos were used for ocular microbiome evaluation. RESULTS: Results are presented as mean ± standard deviation (range). Flamingos comprised 23 females/18 males, aged 11 ± 9.1 (0.7-40) years. Test results: blink rate, 3.7 ± 2 (1-9) blinks/min; PFL, 11.2 ± 1.2 (9-14) mm; IOP, 14 ± 3.2 (10-22) mmHg; EAPPT, 10.2 ± 2.8 (9-14) mm/min; PRTT, 6.8 ± 2.5 (3-13) mm/15 s. Dazzle reflex was positive in four birds examined. Pathologies included cataracts (n = 7 birds), corneal fibrosis (n = 3), endothelial pigment (n = 2), uveal cysts (n = 1), lens luxation (n = 1), and uveitis (n = 1). Ocular microbiome showed high diversity of taxa. CONCLUSIONS: Baseline ocular parameters and incidence of ophthalmic pathology assist veterinarians with disease screening for Chilean flamingos, while the ocular microbiome showed high diversity.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".