The role of gut tissue in the energy metabolism of growing lambs fed forage or concentrate diets
Bibliographic record
Abstract
The role of the gastrointestinal tract (GIT) in explaining the less efficient utilization of metabolizable energy (ME) in growing lambs fed forage rather than concentrate-based diets was investigated by feeding forage (legume-grass silage) and concentrate (whole shelled maize) diets, at isoenergetic intakes (ME basis), using five groups of lambs. One group of seven lambs was an initial slaughter group and of the two groups (eight lambs per group) fed each diet, one group was fed for 8 weeks, whereas the other group was fed for 16 weeks. All lambs were slaughtered between 18.5 and 20 h following their last meal. Retained energy (as a percentage of ME intake) was higher (concentrate-fed 28, forage-fed 17; P<0.001) for the concentrate-fed animals. Weight-specific mucosal O2 uptake (ml/g DM per h), measured in vitro, was 37 % higher for the forestomach (reticulum, rumen and omasum) and small intestine (jejunum) than for the abomasum and large intestine (caecum and colon), but there was no evidence for a diet effect (except colon; forage-fed 5.3, concentrate-fed 4.2; P=0.036). Total GIT heat loss was estimated as 14 (forage-fed) and 18 (concentrate-fed) % of the whole-body heat loss. Although the GIT did not contribute to increased thermogenesis in the forage-fed lambs in the present study, greater relative contribution of GIT tissue to whole-body mass, i.e. GIT as a percentage of empty-body weight(forage 7.6, concentrate 6.6; P<0.001) in the forage-fed animals supports a role for the GIT in contributing to higher thermogenesis observed in ruminants fed forage as opposed to concentrate diets.
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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 | 0.000 |
| 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) | 0.001 | 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".