Application of the law of diminishing returns for partitioning metabolizable energy and crude protein intake between maintenance and growth in growing male and female broiler breeder pullets
Bibliographic record
Abstract
SUMMARY The suitability of diminishing return functions such as the monomolecular and rectangular hyperbola equations, specifically re-parameterized for analysing energy balance data, has been investigated in ruminants, pigs, broilers and turkeys. In the current study, these equations were applied to a total of six time course profiles with male and female broiler breeder pullets (Ross 308 between 1 and 21 weeks of age,n=63 for each sex) in order to provide estimates for energy and protein requirements for maintenance and growth. Non-linear regression was used to estimate parameters and combine them to determine other biological indicators. All statistical computations were implemented in SAS (SAS 2000) by means of the NLMIXED procedure. The best-performing model was identified based on model behaviour when fitting the data, biologically meaningful parameter estimates and statistical performance. In spite of similarity between the biological indicators calculated for each sex using parameter estimates of the two models, quantitative examination of their predictive ability by error measurement indices showed the monomolecular model was superior. The metabolizable energy (ME) and crude protein (CP) requirements for maintenance ranged from 365 to 432 kJ/kg live weight (LW)/d and from 4·3 to 4·9 g/kg LW/d, respectively. The average ME and CP utilization ranged from 11·30 to 12·10 kJ/g body weight (BW) gain and from 0·61 to 0·64 g/g CP intake, respectively. The results obtained using the models were within the range reported by different researchers. Utilization of ME and CP for gain was more efficient at low levels of energy and protein intake, and gradually decreased as the level of energy and protein intakes increased. In conclusion, the models described herein were considered advantageous because they could predict the magnitude and direction of the responses of growing broiler breeder pullets to dietary ME and CP intake, which can be used in choosing and developing special feeding programs to decrease production costs.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".