PSVIII-A-2 How Does the Duration of Low Feed Intake Affect the Ruminant Gastrointestinal tract?
Bibliographic record
Abstract
Abstract The objective of this study was to determine the effect of 5 and 10 d low feed intake (LF) on the ruminant gastrointestinal tract (GIT). Twelve rams and nine wethers were used in a randomized complete block design where they were blocked by castration status and BW. After 5 d of ad libitum feeding, lambs were either exposed to 0 (CON; 100% DMI; n = 7), 5 (LF5; 30% DMI; n = 7), or 10 d (LF10; 30% DMI; n = 7) of LF. At the end of the study, lambs were euthanized, the GIT was removed to determine the digesta and tissue weights by region and the weights of the liver, spleen, and kidneys were recorded. There were no castration × treatment interactions (P ≥ 0.32). Initial (P = 0.97) and final (P = 0.19) BW did not differ by treatment. The weight of the reticulo-ruminal tissue tended to be less (P = 0.06) for LF10 than CON, with LF5 being intermediate but not different. Ruminal digesta weight was not affected (P = 0.98). Omasal tissue weight did not differ among treatments (P = 0.24), but digesta weight tended (P = 0.07) to be greater for CON compared with LF10 and LF5. Abomasal tissue weight was reduced for LF10 (P = 0.04), with LF5 being intermediate but not different. Abomasal digesta weight was less for LF5 and LF10 than CON (P = 0.04). The weight of the duodenum tended (P = 0.08) to be greater for CON than LF10 and LF5, but digesta weight was not affected (P = 0.16). For the jejunum, tissue and digesta weight tended (P = 0.07) to be greater for CON than LF10, with LF5 being intermediate. The weight of the ileum tended to be the greatest for CON, intermediate for LF5, and the least for LF10 (P = 0.10), but digesta weight was not affected (P = 0.81). Cecal tissue weight was not affected by treatment (P = 0.89); whereas digesta weight was the greatest (P = 0.03) for LF10, the least for CON, and intermediate but not different for LF5. In contrast, colonic tissue weight was less for LF10 relative to LF5 and CON (P = 0.01) and digesta weight tended (P = 0.05) to be greater for CON than LF5 and LF10. Liver weight was reduced (P < 0.01) for both LF5 and LF10 relative to CON, but kidney and spleen weights were not affected (P ≥ 0.33). This study indicates that exposing ruminants to LF rapidly reduces the weights for regions of the GIT and liver. These changes likely implicate a reduced absorptive capacity of the GIT and a lesser metabolic capacity of the liver.
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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) | 0.003 | 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".