Metabolic Predictors of Displaced Abomasum in Dairy Cattle
Bibliographic record
Abstract
The objective of this field study was to identify metabolic tests available in clinical practice that identified cows at increased risk of left displaced abomasum (LDA). A technician visited 1044 cows in 20 herds weekly from 1 wk before expected calving until 1 wk postpartum. Cows were assigned a body condition score and samples were collected at each visit for measurement of serum nonesterified fatty acids (NEFA), cholesterol, beta-hydroxybutyrate (BHBA), glucose, urea, calcium, and phosphorus, and a milk sample was collected postpartum for measurement of BHBA. The probability of LDA was modeled with multivariable logistic regression accounting for clustering. There were 53 cases of LDA (incidence risk = 5.1%) and the median time of diagnosis was 11 d in milk. In cows with LDA, mean NEFA concentrations began to diverge from the mean in cows without LDA 14 d before calving, whereas mean serum BHBA concentrations did not diverge until the day of calving. Prepartum, only NEFA concentration was associated with risk of subsequent LDA. Between 0 and 6 d before calving, cows with NEFA concentration > or =0.5 mEq/L were 3.6 times more likely to develop LDA after calving. For prospective application, among samples taken 4 to 10 d before expected calving, the optimum NEFA cut-point remained 0.5 mEq/L. The sensitivity, specificity, and likelihood ratio (LR) were 46%, 82%, and 2.6, respectively. Between 1 and 7 d postpartum, retained placenta, metritis, and increasing serum concentrations of BHBA and NEFA were associated with increased risk of subsequent LDA. However, considered separately, postpartum serum BHBA was a more sensitive and specific test than NEFA concentration. The odds of LDA were 8 times greater in cows with serum BHBA > or =1200 micromol/L (LR = 3.5). Cows with milk BHBA concentration > or =200 micromol/L were 3.4 times more likely to develop LDA. Serum calcium concentration was not associated with LDA. Strategic use of metabolic tests to monitor transition dairy cows should focus on NEFA in the last week prepartum and BHBA in the first week postpartum.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".