In vitro Validation Assessment of a Fecal Occult Blood Protein Test for Horses
Bibliographic record
Abstract
A commercially available equine fecal blood test (FBT) claims to be able to detect the presence of blood proteins (albumin and hemoglobin) in manure. The purpose of this study was to determine the FBT test sensitivity, specificity, positive and negative predictive values (PPV, NPV), lower threshold of detection, time to obtain a visual positive result, effect of temperature and result stability in lab and field conditions. The FBT was assessed for its sensitivity and specificity for detecting pure albumin and hemoglobin at two temperatures over a range of concentrations. Time to result was measured for up to 60 minutes. PPV and NPV were assessed by measuring albumin and hemoglobin in manure from 13 pleasure horses over 25 days. Laboratory tests of hemoglobin alone, albumin alone, and hemoglobin and albumin combined were tested over a range of concentrations from 0.0125 ppm to 50 ppm. In the field study, fresh (within 30 minutes) manure was sampled and tested for proteins using the FBT. The FBT was both sensitive and specific to hemoglobin and albumin. The effect of cold temperature on time to a positive result at 15 minutes was not significant. Results were stable for up to 60 minutes. The field study showed evidence that the appearance of blood proteins in manure was intermittent, and that three tests on consecutive days provided a much better PPV and NPV. It is concluded that this FBT had high specificity, sensitivity, PPV, NPV, was equally functional at low and moderate temperatures, provided a rapid (within 15 minutes) and stable (for up to 60 minutes) reading. Its use in the field is simple and effective.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".