Reliability of 400‐cell and 5‐field leukocyte differential counts for equine bronchoalveolar lavage fluid
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Reliable enumeration of mast cells and eosinophils in equine bronchoalveolar lavage (BAL) fluid is important because small increases in the percentages of these cells support the clinical diagnosis of inflammatory airway disease (IAD). Increases in BAL neutrophils also occur with IAD but are not specific due to overlap between IAD and recurrent airway obstruction (RAO). OBJECTIVES: The objectives of this study were to evaluate the reliability of a standard 400-cell leukocyte differential count and an alternate method evaluating 5 microscopic fields at 500× magnification in equine BAL fluid cytocentrifuged preparations. METHODS: BAL samples from 60 horses with and without pulmonary inflammation were evaluated using 400-cell and 5-field leukocyte differential counting methods. Reliability of enumeration of each leukocyte type was assessed by calculating and comparing intraclass correlation coefficients (ICC). Reliability of mast cell enumeration was further evaluated by comparing ICCs of slides with different cell densities. RESULTS: Reliability was higher for all cell types with the 5-field method; however, overall the difference between methods was not statistically significant. Neutrophil reliability was high (ICC > 0.90) with both methods. Adequate reliability (ICC > 0.85) for mast cells was achieved only with the 5-field method on slides with higher cell density. CONCLUSION: Enumeration of mast cells is unreliable when the standard 400-cell differential counting method is used, whereas the 5-field method on slides with higher cell density reached acceptable reproducibility. Neutrophil percentages were highly reliable with both methods.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it