Modeling chemical and physical body composition of the growing pig
Bibliographic record
Abstract
In pig growth models, masses of body lipid (L) and body protein (P) are key state variables that can be related quantitatively to chemical and phys- ical body composition for predicting growth response and carcass characteristics. The main chemical constit- uents in the empty body weight (EBW) are water (Wa), L, P, and ash. Within pig genotypes, Wa is independent of L and closely related to P (e.g., Wa = × P b ). The scaling parameter (b) is remarkably constant across pig types, at about 0.855, and represents changes in distribution of P with increasing EBW and differences in Wa-to-P ratios among body pools. The parameter a ranges between 4.90 and 5.62 and seems to vary with pig genotype. The ash-to-P ratio, about 0.20, has little significance on estimates of EBW. Gut fill, the differ- ence between live body weight (LBW) and EBW, ranges between 0.03 and 0.10 of LBW; it varies with LBW, feeding level, diet characteristics, and time off-feed. The
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".