Maximizing the performance of heat stressed broilers by optimizing starch-to-lipid ratios, digestible amino acid, and metabolizable energy during the finisher phase
Bibliographic record
Abstract
. Sex-specific starter and grower diets were fed until d 21. The rooms were maintained at 21°C during d 21 to 27. From d 27 to 32, the birds were subjected to cyclical heat stress, with 12 h of 31°C followed by 12 h of 21°C, with a minimum RH of 50 %. BW and feed residual weights were measured on d 21, 27, and 32, then used to calculate BW gain (BWG) and feed-to-gain ratios (F:G). On d 33, 20 birds per treatment per sex were slaughtered to determine carcass characteristics. Under these conditions (d 21 to 32), maximum male BWG of 926 g was estimated to occur when fed a diet comprised of 42.2 % Basal B and 57.8 % Basal C with a S:L ratio of 4:1, AME of 3089 kcal/kg, and 1.01 % DigLys. Diet did not influence female BWG during heat stress. Although a practical recommendation was not possible for optimal breast meat yield (% live weight) and F:G ratios, the results, indicated that increasing DigLys would improve these parameters under heat stress.
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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".