Comparison of mathematical and comparative slaughter methodologies for determination of heat production and energy retention in broilers
Bibliographic record
Abstract
Understanding factors affecting ME availability for productive processes is an important step in optimal feed formulation. This study compared a modelling methodology with the comparative slaughter technique (CST) to estimate energy partitioning to heat production and energy retention (RE) and to investigate differences in heat dissipation. At hatch, 50 broilers were randomly allocated in one of 4 pens equipped with a precision feeding station. From day 14 to day 45, they were either fed with a low-ME (3,111 kcal/kg ME) or a high-ME (3,383 kcal/kg ME) diet. At day 19, birds were assigned to pair-feeding in groups of 6 with lead birds eating ad libitum (100%) and follow birds eating at either 50, 60, 70, 80, or 90% of the paired lead's cumulative feed intake. Heat production and RE were estimated by CST and with a nonlinear mixed model explaining daily ME intake (MEI) as a function of metabolic BW and average daily gain (ADG). The energy partitioning model predicted MEI = (145.10 + u) BW0.83 + 1.09 × BW−0.18 × ADG1.19 + ε. The model underestimated heat production by 13.4% and overestimated RE by 22.8% compared with the CST. The model was not able to distinguish between net energy for gain values of the diets (1,448 ± 18.5 kcal/kg vs. 1,493 ± 18.0 kcal/kg for the low-ME and high-ME diet, respectively), whereas the CST found a 148 kcal/kg difference between the low-ME and high-ME diets (1,101 ± 22.5 kcal/kg vs. 1,249 ± 22.0 kcal/kg, respectively). The estimates of the net energy for gain values of the 2 diets decreased with increasing feed restriction. The heat increment of feeding did not differ between birds fed with the low- or high-ME diet (26% of MEI). Additional measurements on heat dissipation, physical activity, and immune status indicated that the energetic content of the diet and feed restriction affect some parameters (shank temperature, feeding station visits) but not others (leukocyte counts, heterophil to lymphocyte ratio, and immune cell function).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".