Comparison of flow cytometry and immunofluorescence microscopy for the detection of <i>Giardia duodenalis</i> in bovine fecal samples
Bibliographic record
Abstract
The performance of flow cytometry (FC) was compared with immunofluorescence microscopy (IM) for detection of Giardia duodenalis in bovine feces. Samples from 36 adult dairy cows and 208 dairy calves were collected. Flow cytometry test characteristics were calculated using continuous, ordinal, and dichotomized results. Spearman correlation coefficients comparing the results of the 2 tests were 0.47 and 0.68 for cows and calves, respectively. Using IM as indicative of presence or absence of G. duodenalis cysts in each sample, likelihood ratios of FC results with 0, 1, and > or = 2 gated events indicated that samples with 1 gated event were likely to be positive in the cows but not in the calves. Immunofluorescence microscopy detected G. duodenalis in 69.7% and 48.1% of cows and calves, respectively. When dichotomizing the FC results at a cut-off point of 1 or 2 gated events, 46.3% and 19.9% of the cow and 51.9% and 35.1% of the calf samples, respectively, were classified as G. duodenalis-positive. Relative to IM, the sensitivity in the cows was 0.59 and 0.28, respectively, and 0.76 and 0.64, respectively, in the calves. At a cut-off point of 1, 65.7% and 73.1% of the cow and calf samples, respectively, were correctly classified in FC, and at a cut-off point of 2, 49.3% and 78.4% were correctly classified in the cows and calves, respectively. Flow cytometry was less sensitive than IM. Possible reasons and research needed to improve FC for G. duodenalis detection are discussed.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".