Multiattribute Evaluation of Two Simple Tests for the Detection of Cryptosporidium parvum Oocysts in Calf Feces
Bibliographic record
Abstract
Cryptosporidium parvum is increasingly recognized as an important pathogen in neonatal dairy calves. As a result, there is a need for simple, inexpensive and quick methods for the detection of C. parvum infection in calf feces. Most diagnostic and screening methods for this parasite that are currently in common use, such as concentration and staining methods and immunofluorescence (Kvac et al, 2003), are expensive and time-consuming, and as such are unsuitable for the screening of large numbers offecal samples in veterinary practice or research. At the Ontario Veterinary College (OVC), a simple sucrose wet mount method without centrifugation has been in use for some time. However, to the authors' knowledge, there are no published reports that have evaluated the performance and utility of this method when used for the detection of C. parvum oocysts in calf feces. In this study, the OVC sucrose wet mount method and a lateral immunochromatography test for detection of C. parvum antigen in feces (BioX Diagnostics, Jem~lle, Belgium) were evaluated using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) with gel electrophoresis as a gold standard.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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 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".