159 Effect of dry or Temper Rolling of High or low Protein Wheat and its Impact on Rumen Parameters, Liver Abscesses, and Growth Performance of Feedlot Cattle
Bibliographic record
Abstract
Abstract The objective of this study was to assess the impact of low (13%, LP) or high protein (18%, HP) wheat grain subjected to dry (DR) vs temper rolling (TR) on growth performance, rumen parameters, and liver abscesses of feedlot steers. A backgrounding (BG) to finishing (FN) feedlot trial was performed using 160 302 ± 34 kg; 24 ruminally cannulated) Angus steers blocked by weight and randomly assigned to 16 pens. Cannulated steers (3 per pen) were housed within 8 pens equipped with a feed intake monitoring system. BG diets contained 35% wheat grain, 60% barley silage, and 5% supplement on a DM basis. Transition (TN) diets included sequential increases to the proportion of wheat grain in the total mixed ration to achieve a FN diet comprised of 85% wheat grain, 10% barley silage, and 5% supplement. Rumen pHs were measured with an indwelling logger and rumen samples were collected in each phase. Steers fed the HP-DR and LP-TR diets had lower (P≤0.03) ruminal pH than HP-TR during the TN phase. Tempering HP wheat reduced (P<0.001) the generation of fine particles during rolling. During BG and TN, steers fed diets containing HP wheat had higher (P<0.001) ruminal NH3 concentrations than the LP treatments. NH3 measurements during the FN phase were higher (P=0.01) for the LP-DR treatment compared to the LP-TR treatment. Greater (P≤0.01) C2:C3 ratios were noted for HP wheat diets during the BG and FN phases whereas the C2:C3 ratio was reduced (P<0.001) with TR wheat during the FN phase. Greater (P= 0.01) NEgs were assessed for FN steers fed LP wheat. Steers fed HP wheat had more severe (P<0.001) abscesses. Results suggest that HP wheat may limit the growth performance of FN cattle and increase the severity of liver abscesses.
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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".