Accuracy of a new milk strip cow-side test for diagnosis of hyperketonemia
Bibliographic record
Abstract
The objectives of this study were to determine the accuracy of the PortaBHBTM milk strip for detection of hyperketonemia in early lactation cows, and to compare the agreement of results from quarter and composite samples. A total of 577 Holstein cows of all parities, from 88 commercial herds, were sampled once during this study. Cows were sampled simultaneously for blood and milk between one and 60 days-in-milk. Blood samples were collected from coccygeal vessels, and were analyzed on-farm using an electronic ?-hydroxybutyrate (BHBA) hand-held meter. Milk samples were collected from one quarter (n=577), as well as from four quarters (composite; n=299). All milk samples were tested using PortaBHBTM milk strips (0, 50, 100, 200, and 500 æmol/L). Blood BHBA concentration was considered to be the gold standard, with hyperketonemia denned as a blood BHBA concentration ?1400 æmol/L. With this cut-point, the true prevalence of hyperketonemia in the study population was 24.6%. Using a threshold of 100 æmol/L, sensitivity and specificity of PortaBHBTM milk strips was 89.2% and 79.6%, respectively. Using a threshold of 200 æmol/L, sensitivity and specificity of PortaBHBTM milk strips was 40.3% and 99.5%, respectively. The kappa coefficient for agreement between milk results from quarter and composite samples, using a threshold of 100 æmol/L, was 0.95. Study results suggest that PortaBHBTM has good accuracy, and that there is no benefit to collect milk samples from four quarters compared with sampling one quarter.
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How this classification was reachedexpand
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".