Response of Broilers to Graded Levels of Distillers Dried Grain
Bibliographic record
Abstract
A total of one hundred (100) day old broilers of mixed sexes were used to investigate the effects of graded levels of distillers dried grain on performance, nutrient utilization, and carcass evaluation. The birds were randomly allocated to five treatment groups of 20birds, and were further replicated five times. The five treatments comprised of graded levels of Distiller Dried Grain (DDG) in 0, 10, 20, 30 40% inclusion to replace maize. Feed intake, weight gain and feed/gain ratio were significantly affected (P<0.05) by levels of DDG. Average daily feed intake increased with increasing levels of DDG. Birds fed 40% DDG had the highest (72.90g/bird/day) feed intake while the birds on the control diet had the lowest (68.04g/bird/day) feed intake. Weight gain was significantly affected (P<0.05) by dietary DDG. Birds fed 10% DDG had the highest weight gain (27.95g/bird/day). Beyond this dietary inclusion level (10%), weight gain continued to decrease. Birds fed 40% DDG had the lowest weight gain (23.10g/bird/day). Nutrient retention was significantly affected (P<0.05) by dietary DDG. Protein and fat retention decreased with increase in level of dietary DDG. These nutrients were retained more by broilers fed 10% dietary level of DDG. Dietary levels of DDG had no significant influence (P<0.05) on the relative weight of the different body parts. It was concluded that up to 10% DDG can be used in broiler starter and finisher diet.
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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 | 0.001 |
| 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".