The effect of tissue mobilization and stage of lactation on energy partitioning in lactating sows: an analysis of commercial data
Bibliographic record
Abstract
Abstract The objective of this paper was to investigate how the predicted level of body energy mobilized and the stage of lactation affects performance and energy partitioning in lactating sows kept under commercial conditions. Seventy-seven lactating sows from three consecutive batches were weaned at 28 d and all measures were taken over the first 20 d. Total feed consumption was measured and sows’ live weight was registered when entering the lactation facilities and at 21 d of lactation. Blood samples were collected at farrowing and once a week thereafter. Net energy (NE) mobilization or loss was calculated by difference using the general NRC equation for ME partitioning. Compared to low mobilizers (low NE loss values), high mobilizing sows had lower feed intake and higher loss of live weight, body fat and body protein. High mobilizers also weaned more piglets and had heavier litters than low mobilizers. Energy mobilization (NE loss) was higher from day 1 to 10 of lactation compared to day 11 to 20, and the difference in mobilized energy between high and low mobilizing sows was also higher in the first than in the second half of lactation. Body weight and back fat thickness losses were significantly correlated with NE loss. A more accurate prediction of the changes in live weight or back fat thickness over lactation should help better predict total amount of energy mobilized, and more research is needed to assess the relative contribution of lean and fat to mobilized tissue.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".