Effects of alternate day supplementation at two levels of energy on forage utilization and performance of growing steers grazing stockpiled cool-season perennial grass pastures
Bibliographic record
Abstract
Abstract This study was conducted to evaluate the effects of supplementing energy daily vs. on alternate days at two levels (1.5× and 2× daily amount) on forage utilization and performance of growing steers grazing stockpiled cool-season perennial grass (CSPG) pasture. Forty-five crossbred yearling steers were stratified by initial body weight (BW) (358 ± 18 kg) and randomly assigned to one of the nine CSPG pasture paddocks (5 steers paddock−1). Each paddock was randomly assigned to one of the three replicated (n = 3) supplementation strategies. A pelleted feed (30.3% neutral detergent fibre; 32.0% starch; 7.2% crude fat) was formulated to provide 3.2 Mcal kg−1 of digestible energy and offered daily (DLY) at 0.6% of BW, or on alternate days at two levels: 0.9% [low alternate (LA)] and 1.2% [high alternate (HA)] of BW. After a 70 d grazing period, forage utilization of DLY (65.2%) was not different (P ≥ 0.69) when compared with LA (63.7%) or HA (65.0%). Also, final BW and cumulative average daily gain of DLY (435 kg and 1.1 kg d−1) were not different (P ≥ 0.11) when compared with those of LA (424 kg and 0.9 kg d−1) or HA (428 kg and 1.0 kg d−1). These results suggest that it is possible to reduce the frequency and amount of energy supplementation in grazing-growing cattle without reducing animal performance.
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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".