Effect of Three Colostrum Diets on Passive Transfer of Immunity and Preweaning Health in Calves on a California Dairy following Colostrum Management Training
Why this work is in the frame
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Bibliographic record
Abstract
Following colostrum management training, a randomized field trial was conducted on a California dairy to determine the effect of supplementing pooled colostrum with either colostrum-derived replacer (CDR) or second-milking colostrum (transition milk) on failure of passive transfer (FPT) and preweaning morbidity risks. A total of 166 calves were randomly assigned to 4L first-milking pooled colostrum (treatment 1), 2L first-milking pooled colostrum and 2L of CDR (treatment 2), or 2L first-milking pooled colostrum and 2L second-milking pooled colostrum (treatment 3). Mean 24-hour serum TP and IgG for treatments 2 (TP 5.2 g/dL, IgG 15.9 g/L) and 3 (TP 5.4 g/dL, IgG 18.3 g/L) did not statistically differ but were significantly lower than for treatment 1 (TP 5.9 g/dL, IgG 24.6 g/L). Risk of FPT did not differ for treatments 1, 2, and 3 (0.0%, 9.3%, and 1.9%, resp.). Similarly, the preweaning risk of diarrhea (81.0%, 92.5%, and 87.0%, resp.) or pneumonia (6.9%, 13.2%, and 18.5%, resp.) did not differ between treatments. Feeding 4L first-milking pooled colostrum resulted in adequate passive transfer. When first-milking pooled colostrum quantity is inadequate, CDR or second-milking pooled colostrum can be used to supplement the required colostrum volume and IgG mass without adversely affecting the risks of FPT or preweaning diarrhea and pneumonia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it