Estimation of Growth Curves and Suitable Slaughter Weight of the Liangshan Pig
Bibliographic record
Abstract
The Liangshan pig is a traditional Chinese small-sized breed; it has a relatively long feeding period and low meat production ability but superior meat quality. This study utilized three non-linear growth models (Von Bertalanffy, Gompertz, and logistic) to fit the growth curve of Liangshan pigs from an unselected, random-bred pig population and estimate the pigs most suitable slaughter weight. The growth development data at 20 time points of 275 Liangshan pigs (from birth to 250 d) were collected. To analyze the relative gene expression related to development, seven slaughter weight phases (50, 58, 66, 74, 82, 90, and 98 kg) (20 pigs per phase) were examined. We found that the Liangshan pig growth curve fit the typical S-curve well and that their growth turning point was 193.4 days at a weight of 62.5 kg, according to the best fit Von Bertalanffy model based on the goodness of fit criteria. Furthermore, we estimated that the most suitable slaughter weight was 62.5 to 74.9 kg based on the growth curve and the relative expression levels of growth-related genes.
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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".