Factors associated with serum vitamin A and E concentrations in beef calves from Alberta and Saskatchewan and the relationship between vitamin concentrations and calf health outcomes
Bibliographic record
Abstract
The study objectives were to identify factors associated with serum vitamin A and vitamin E concentrations in beef calves less than 1 mo old and to examine associations between vitamin concentrations and health outcomes. Serum vitamin A concentrations were highest in calves more than 4 d old, with serum immunoglobulin G concentrations > 19 g L−1, from cows without perinatal health problems, and born where precipitation in the previous growing season was ≥200 mm. Serum vitamin E was highest in calves more than 4 d old, born earlier in the calving season, not born to heifers, and that received selenium and vitamin E injections at or shortly after birth. After accounting for other risk factors, calves with serum vitamin A less than 0.14 μg mL−1 were 2.8 times more likely to die (P = 0.02), and calves with serum vitamin E less than adequate for their age (2–7 d old, <0.8 μg mL−1; >7 d old, <0.5 μg mL−1) were 3.2 times more likely to be treated for enteritis than calves with higher concentrations (P = 0.0001). Drought conditions, dam peripartum health problems, and inadequate colostrum intake contribute to low vitamin A and vitamin E concentrations and adverse health outcomes in beef calves.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".