156 Effect of Increasing Levels of Ergot Alkaloids in the Diet of Feedlot Cattle
Bibliographic record
Abstract
Abstract This study evaluated the effects of feeding ergot alkaloids (EA) at increasing levels (0, 0.75, 1.5, and 3.0 ppm) to feedlot beef cattle over backgrounding (BG) and finishing (FS) phases on growth performance and carcass quality. Steers (n=240; 280±32 kg) were blocked by weight and randomly allocated to 16 pens (4 pens/treatment; 15 steers/pen). Treatments included: no added EA (CTL); or EA added at 0.75 (EA075); 1.50 (EA150); and 3.0 ppm (EA300). Steers were fed barley-based BG diets containing 40% concentrate:60% silage (DM basis) for 84 d, then stepped up over 28 d to a 90% concentrate:10% silage (DM basis) FS diet for 119 d. Steers fed EA300 received CTL in FS after 77 days on feed (DOF). In the BG phase, a quadratic decrease (P=0.05) in ADG and a linear decrease in final BW (P=0.03) and total BW gain (P=0.02) were observed with increasing EA. In the FS phase, up to 77 DOF, there was a linear decrease in steers DMI (P=0.04), ADG (P=0.01), and total BW gain (P=0.01) with increasing levels of EA. Over the full FS phase (119 DOF), a quadratic response was observed for ADG (P=0.05), final BW (P=0.05), total BW gain (P=0.02) and carcass weight (P=0.05) with steers fed EA150 showing the lowest performance. Gain:feed was not affected (P>0.20) by EA in the BG or FS phase. Dressing percentage (P=0.02) showed a quadratic effect with EA300 being the lowest. Additionally, a linear increase in lean meat yield (P< 0.001) was observed with increasing EA. Including EA in the diet promoted a linear increase in rectal temperature (P< 0.01). In conclusion, increasing levels of EA in the diet reduced growth performance, but when EA was removed, steers showed compensatory weight gain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".