Variability of colostrum yield and colostrum intake in pigs
Bibliographic record
Abstract
Colostrum yield and composition of 40 Landrace×Large White sows were determined from the onset of parturition until 24 h post partum. Colostrum yield was calculated by adding individual piglets' colostrum intakes for each litter. Colostrum was assayed for prolactin, progesterone, oestradiol-17β, immunoglobulin G and its nutritional composition was determined. Piglets' individual colostrum intake averaged 300 ± 7 g and sows' colostrum yield averaged 3.67 ± 0.14 kg (minimum 1.91 kg, maximum 5.31 kg). Live weight and characteristics at birth (umbilical cord already ruptured, splayleg, difficulty to breathe) were the major factors influencing individual colostrum intake. Colostrum yield was not affected by litter size, tended to be influenced by parity (P = 0.059) and was lower when farrowing was induced (P = 0.017). On the other hand, no relationships were found between hormone concentrations in colostrum and colostrum yield. Mean piglet birth weight and litter weight variation at birth were related to colostrum yield (r = 0.38; P = 0.015 and r = -0.34; P = 0.030, respectively). These results suggest that determinism of colostrum yield depends, in part, on global vitality of the litter but seems to be, most probably, affected by the capacity of sows to produce enough colostrum for the whole litter. Further studies are needed to understand the endocrine regulation of colostrum secretion in sows.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".