Fine-needle aspiration in the diagnosis of equine skin disease and the epidemiology of equine skin cytology submissions in a western Canadian diagnostic laboratory.
Bibliographic record
Abstract
Fine-needle aspiration (FNA) is commonly used to diagnose skin disease in companion animals, but its use in horses appears to be infrequent. Equine veterinarians in western Canada were surveyed to determine their opinions about FNA and 15 years of diagnostic submissions were used to compare the perceived to actual value of FNA in the diagnosis of skin disease in horses. Practitioners viewed FNA as quick, easy, economical, and minimally invasive. However, most veterinarians rarely chose to use FNA due to a perception that sample quality and diagnostic yield were poor and there was a narrow range of diseases the technique could diagnose. Analysis of the FNA cytology samples from a veterinary diagnostic laboratory showed a wide variety of equine skin disease conditions, but the frequency of non-diagnostic results was significantly higher in equine submissions compared to those from dogs and cats.
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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 | 0.008 |
| 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) | 0.000 | 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".