Evaluation of the Precision Xtra meter for monitoring blood β-hydroxybutyrate concentrations in late-gestation ewes
Bibliographic record
Abstract
Blood samples were collected from late-gestation ewes to determine the agreement of a point-of-care (POC) Precision Xtra meter and a standard laboratory test for β-hydroxybutyrate (BHBA). Fresh whole blood samples were immediately tested with the POC instrument, and serum samples were analyzed with a standard commercial biochemical analyzer. Ewes were classified as having ketonemia if their BHBA concentrations were ≥800 µmol/L. Scatter plots, paired t-tests, Bland-Altman limits of agreement, and Gwet AC1 tests were used to compare results. The 2 tests had very good agreement. The values between instruments were not statistically different based on paired t-tests ( p = 0.312). The intercept and slope of a linear mixed model, containing the standard test results as an outcome and the POC meter results as a predictor, were 0.02 (95% CI: 0.00, 0.04) and 0.98 (95% CI: 0.96, 1.01), respectively. When the samples were classified into ketonemic classes (non-ketonemic and ketonemic) based on BHBA concentrations obtained from each test, the Gwet AC1 statistic was 0.94 (95% CI: 0.91, 0.97; p < 0.001). The ketosis classification agreed in 95% of samples. Based on the Bland-Altman plot and limits of agreement, the optimal cutoff to diagnose ketonemia with the POC meter was 1,000 µmol/L, which is 200 µmol/L higher than the laboratory BHBA medical decision limit. The Precision Xtra meter provided excellent correlation and substantial agreement with the standard laboratory technique for measuring blood BHBA in late-gestation ewes.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".