Characterization of whole body compositional growth of male ducks during the twenty-nine day post-hatch period
Bibliographic record
Abstract
Schinckel, A. P., Einstein, M. E., Ajuwon, K. M. and Adeola, O. 2013. Characterization of whole body compositional growth of male ducks during the twenty-nine day post-hatch period. Can. J. Anim. Sci. 93: 113–122. Changes in whole body dry matter, lipid, ash, energy, crude protein, and amino acids were evaluated during a 29 d post-hatch period in White Pekin ducks. Drakes were assigned to slaughter 1, 8, 15, 22, or 29 d post-hatch with four replicates of four ducks per slaughter period. The body weight (BW) data were fitted to the Weibull function with the form:[Formula: see text]where BWit is the BW of the ith duck at t days of age and A, B, C, and IP are parameters. The value of IP, the inflection point, which minimized the residual SD, was 40 d. Values of A (8591 g, SE=190), B (42.87, SE=11.5), and C (1.7399, SE=0.050) resulted in an R 2 of 0.9836 and residual SD of 83.7 g. Allometric (Y=A BWB), linear-quadratic and exponential (Y=exp (b0+b1BW+b2 (BW)2) functions of BW were fitted to the chemical component and amino acid mass data. Dry matter percentage of the ducks increased (P<0.01) with age. The protein content of the dry matter decreased (P<0.01) from day 1 to day 8 (69 to 58.2%) and then increased to 60% by d 29. Concentrations of several amino acids were affected (P<0.05) by age. The predicted accretion rates of Lys, Trp, and Met relative to protein accretion increased as age increased. The predicted daily accretion rates for major indispensable amino acids increased rapidly the first 5 d post-hatch and subsequently increased but at a decreasing rate to day 29 post-hatch. The relative growth rates of chemical components and indispensable amino acids were affected by age indicating that the nutrient requirements of ducks differ from day 1 to day 29 post-hatch. Compositional growth and amino acid accretion data can be used to model the nutrient requirements of ducks.
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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 | 0.001 | 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 | 0.001 |
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".