Pigs weighing less than 20 kg are unable to adjust feed intake in response to dietary net energy density regardless of diet composition
Bibliographic record
Abstract
This study was conducted to investigate the effects of increasing dietary net energy (NE) density manipulated by either dietary fat or fibre content on growth performance and energy intake in weaned pigs. A total of 60 barrows (8.40 ± 0.91 kg) were randomly allotted to one of five dietary treatments based on initial body weight. The experimental diets contained increasing NE densities (i.e., 9.9, 10.3, and 10.7 MJ NE kg−1) by manipulating either dietary fat or fibre content. Feeding the different dietary treatments did not affect growth performance among dietary treatments. The apparent total tract digestibility of dry matter, gross energy, fat, and neutral detergent fibre of the diets linearly increased (P < 0.05) for weeks 1–3 as dietary NE densities increased. Digestible energy (DE) and NE intake linearly increased (P < 0.01) with increasing dietary NE densities manipulated by dietary fibre content for weeks 2 and 3. A tendency (P = 0.06) for a linear increase in DE and NE intake was observed for weeks 2 and 3 when dietary NE densities were manipulated by fat content. In conclusion, weaned pigs were not able to adjust feed intake in response to dietary NE densities ranging from 9.9 to 10.7 MJ kg−1.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".