The effects of weaning weight and rate of growth immediately after weaning on subsequent pig growth performance and carcass characteristics
Bibliographic record
Abstract
Effect of accelerated weight gain immediately after weaning on subsequent performance was evaluated in pigs with heavy and light weaning weights. The study was carried out as a randomized complete block design with a 2 × 2 × 2 factorial arrangement with the treatments being weaning weight (Heavy vs. Light), post-weaning growth rate (Accelerated vs. Conventional) and sex (Barrow vs. Gilt). Pigs were weaned at 18 to 22 d of age, weighed and classified as either Heavy or Light (5.4 vs. 3.9 kg, SE ± 0.04). During the first 14 d after weaning, pigs on the Accelerated growth treatment were housed in a specialized nursery and provided with liquid milk replacer and a dry diet; pigs on the Conventional treatment were housed in a standard nursery and provided with a dry diet only. Subsequent to the 14 d post-weaning treatment period, pigs from all treatments were housed in standard accommodation and provided the same dietary regimen to slaughter weight (110 kg). Pigs on the Accelerated treatment were heavier (P < 0.01) than pigs on the Conventional treatment at the end of the treatment period (9.2 vs. 8.1 kg, SE ± 0.13) and at 56 d of age (19.6 vs. 18.3 kg, SE ± 0.28). Early growth rate did not affect growth from 35 d of age to slaughter weight, or days to reach slaughter weight. Pigs on the Conventional treatment had greater (15.6 vs. 14.1 mm, SE ± 0.47, P < 0.01) backfat depths at slaughter than those on the Accelerated treatment. Heavy pigs at weaning were heavier (P < 0.001) at birth and 56 d of age than light pigs, and reached slaughter weight 8.6 d earlier (P < 0.001). In summary, weaning weight, but not growth rate in the first 2 wk after weaning, influenced age at slaughter. Key words: Pigs, weaning weight, post-weaning growth rate, weaning management
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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) | 0.001 | 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 | 0.001 |
| 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".