Can feeding behaviour explain part of the variation observed in growing pigs’ body composition?
Bibliographic record
Abstract
This study focused on the relationship between feeding behaviour and the composition of the body gain in growing pigs. Feeding behaviour and body composition traits were calculated using individual information from 165 pigs during the last 28 days of the finishing period of 3 growing trials. A linear regression model describing the relationship between relative cumulated feed intake (CFI) and time of each pig was used to calculate a new index (DAreg) representing the regularity of feeding behaviour. Across studies, moderate and significant (P<0.001) correlations were found between DAreg and FV (r=-0.57) and IFV (r=0.55). Correlations between feeding behaviour traits and the % of protein and lipid of the body gain were weak. Additionally, behavioural traits including DAreg explained only 17% of the variation of the proportion of lipid on body gain. Other factors than feeding behaviour are modulating growing pigs' body composition.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 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".