0963 Effects of feeding dried cabbage residues on performance, ileal and total tract digestibility, and selected microbial population in broiler chickens
Bibliographic record
Abstract
A study was conducted to investigate the effects of partially replacing corn and soybean meal with dried cabbage leaf residues (DCR) on broiler growth performance, apparent ileal nutrient digestibility and apparent total tract nutrient utilization. Dietary treatments include 4 levels of DCR (0, 3, 6, and 9%). Two hundred and twenty four 1-d old male broilers were randomly assigned to 1 of 4 groups (8 cage replicates; 7 birds/cage) and grown over a 35-d experimental period. Results showed that feeding DCR had no effects on daily body weight gain (average 53.4 g/d), daily feed intake (average 94.9 g/d), and feed conversion ratio (average 1.78 g of feed/g of gain). Inclusion of DCR reduced apparent ileal DM (quadratic effect, P < 0.001), OM (linear effect, P = 0.012), and CP (quadratic effect, P = 0.001) digestibility of younger birds (d 21) while incremental levels of DCR had no effect on apparent ileal nutrient digestibilities of older birds (d 35). Apparent total tract digestibility of DM, OM, and CP increased (linear effect, P < 0.001) as the level of DCR increased. It was concluded that the inclusion of DCR in broiler diets up to 9% had no negative impact on bird performance and apparent ileal digestibility of older birds and improved apparent total tract nutrient digestibility.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".