Bibliographic record
Abstract
The aim of this study is to model and analyse a dynamic of feed conversion coefficient in pigs' ontogeny. Feed conversion is a process that couples feed intake, and growth. While there has been much research into the problem, a quantitative relation between the traits has not been revealed. The study considers feed as nutrient weight rather than its energy or a separate feedstuff. A main task of the research is to find out an analytical function between the traits. It is expected that the study will provide a new insight into the problem. Animals are open systems; they need feed to sustain life, to grow and develop. It is plausible to suppose that growth of animal is a function of feed conversion and body weight. To find out and analyse this function a deterministic model of growth was built. The model was built as a dynamic system that describes the growth of individual animals. Both continuum and discrete-time modelling techniques are employed. The model is based on a data set obtained in experiments and field observations. Theoretical notions about the growth have been used for the model analyses. It is shown that in ontogeny feed conversion and growth rate are functionally related traits. Between the traits, there is a nonlinear relation that concerns the growth rate, and feed conversion coefficient. In the model, the feed conversion coefficient is the variable that determines the dynamic of growth.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".