Cytological analysis of bronchoalveolar lavage fluid acquired by bronchoscopy in healthy ferrets: A pilot study.
Bibliographic record
Abstract
The objective of this study was to investigate the normal cytological evaluation of bronchoalveolar lavage (BAL) fluid in healthy adult ferrets (N = 12). These ferrets underwent bronchoscopy and BAL using sterile saline [1.5 mL/kg body weight (BW)]. Percentage of fluid recovered, total leukocyte count, differential leukocyte count, and cell count of the epithelial lining fluid (ELF) were determined. The mean percentage of lavage volume recovered from the right lung and left lung were 67.8 ± 14.9% and 69.7 ± 20.0%, respectively. Gender (P = 0.12) and weight (P = 0.17) did not significantly affect the mean percentage of recovered volume. The mean percentage of recovered volume (P = 0.47) and the mean leukocyte count (P = 0.17) from the right and left lung were not significantly different. Macrophages were the main leukocyte component of the lavages, followed by neutrophils, lymphocytes, and eosinophils. The mean proportion of ELF in BAL fluid was 9.3 ± 3.7% v/v. Bronchoscopy is clinically useful for collecting good quality BAL samples for cytological analysis in ferrets. The leucocyte differential was established, which may help veterinarians to make better clinical decisions when treating respiratory disease. Further studies are required with a larger group in order to establish the healthy reference intervals for BAL values in ferrets.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".