Research on the influence of density from pen on growth parameters recorded at pigs that are used for the production of bacon.
Bibliographic record
Abstract
The purpose of this study was to establish the influence of density from pen on the production performance registered in a pig breeding unit for bacon. The biological material consisted of xYorkshire Landrace x Duroc triracial Metis (LYD) divided into two batches: L1 21 animals per pen and L2 26 animals per pen. The following parameters were observed: the dynamics of weight gain, average daily gain, feed consumption during growth and fattening period, the feed conversion index and the actual losses and their causes. The dynamics of the body weight shows a superiority of the batch: L1 (99, 4 kg) to batch L2 (97.8 kg), which represents a difference of 1.63%. Also in the case of other studied parameters (the average daily weight gain, feed consumption, feed conversion) the batch that was formed from 21 specimens/pen (L1) registered high performances in comparison with batch L2 (26 specimens/pen). The results that were obtained confirm the fact that the density of the pens influences the productive performances of the pigs. On the basis of the data we recommend that the pigs are kept in effectives of 20-21 specimens per pen in order to obtain better productive and economic results.
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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 | 0.001 | 0.001 |
| 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".