Short communication: The effect of temperature on performance of milk ketone test strips
Bibliographic record
Abstract
Ketosis is estimated to affect 15% of early lactation dairy cows. A ketone test strip (Keto-Test; Elanco Animal Health, Greenfield, IN) allows producers a method to determine the concentration of β-hydroxybutyrate (BHBA) in milk to track individual animal and herd incidence of ketosis. The objective of this study was to determine the effect of altering the temperature of milk and the test strips at the time of the test on the reliability of the Keto-Test. A total of 118 Holstein cows, ranging from 5 to 17 DIM, were selected from a commercial Holstein dairy herd in Michigan. A milk sample was collected from the right rear quarter of each cow during the a.m. milking. Each sample was tested under 4 temperature conditions: (1) Keto-Test strips and milk at room temperature (RT; 24.0 ± 0.1°C; control; manufacturer's instructions), (2) cold strips (10.8 ± 0.9°C) and milk at RT, (3) cold strips and fresh milk, and (4) strips at RT and fresh milk. Milk was recorded as negative (0-99 μmol/L), weak positive (100-199 μmol/L), positive (200-499 μmol/L), or highly positive (≥ 500 μmol/L). Blood samples were collected immediately following milk collection and analyzed for BHBA concentration using a ketone test meter. Cows with blood BHBA concentration of ≥ 1,400 μmol/L were considered positive for subclinical ketosis. Accuracy of the Keto-Test strips under the 4 conditions was determined by the κ coefficient of agreement, using the result of condition 1 as the accepted true value. Additionally, sensitivity and specificity were calculated using the blood BHBA concentrations and results of each of the 4 conditions. Using the Keto-Test 60.2% of cows tested negative for milk BHBA, 24.6% tested weak positive, 14.4% tested positive, and 0.8% tested highly positive. The weighted κ coefficient of agreement between the control condition (1) and condition 2, 3, and 4 and 95% lower and upper confidence intervals were as follows: condition 2=0.71 (0.62, 0.80), condition 3=0.69 (0.60, 0.78), and condition 4=0.63 (0.54, 0.73). These results indicate good agreement between the outcome of condition 1 and conditions 2, 3, and 4. The sensitivities/specificities for 1, 2, 3, and 4 were as follows: 0.77/0.79, 0.74/0.75, 0.69/0.88, and 0.69/0.84, indicating that the test in all temperature conditions had a strong ability to detect the presence of BHBA in milk. In conclusion, the reliability of the Keto-Test strips was not dependent on the temperature of the milk or the test strips.
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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 | 0.002 | 0.006 |
| 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) | 0.002 | 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".