Peripartum Serum Vitamin E, Retinol, and Beta-Carotene in Dairy Cattle and Their Associations with Disease
Bibliographic record
Abstract
Peripartum decreases in serum concentrations of vitamins A and E may contribute to impaired immune function in dairy cows. The objectives of this study were to describe peripartum serum concentrations of alpha-tocopherol, beta-carotene, and retinol and their associations with disease risk. On 20 farms over 1 yr, blood samples were collected weekly from 1057 cows from 1 wk before expected calving until 1 wk postpartum. Serum concentrations of alpha-tocopherol, beta-carotene, and retinol, as well as several biochemical variables were measured. Their associations with the risk of retained placenta or clinical mastitis were modeled separately with logistic regression, and the factors associated with the concentration of each vitamin were modelled with mixed linear regression. Differences in vitamin concentrations between 2 batches of sera analyzed 6 mo apart required stratification of statistical analyses. Accounting for the effects of parity, season, and twins, an increase in alpha-tocopherol of 1 microg/mL in the last week prepartum reduced the risk of retained placenta by 20%, whereas serum nonesterified fatty acid concentration > or = 0.5 mEq/L tended to increase risk of retained placenta by 80%. In the last week prepartum, a 100 ng/mL increase in serum retinol was associated with a 60% decrease in the risk of early lactation clinical mastitis. There were significant positive associations of peripartum serum concentrations among each of alpha-tocopherol, beta-carotene, and retinol.
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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 | 0.001 | 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 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".