Plasma leptin as a predictor for carcass composition in growing lambs
Bibliographic record
Abstract
The experiment was conducted on 30 single born Polish Merino ram lambs. At the age of 112 d, 10 ram lambs were slaughtered at 20 kg (group 1), 25 kg (group 2), and 30 kg (group 3) live weight. Plasma leptin increased between 20 and 25 kg, as well as 25 and 30 kg live weight. The differences between group 1 vs. group 3 and group 2 vs. group 3 were statistically important (P < 0.001). The lack of differences in meat content of the pelvic limb between the groups and, at the same time, the lower fat content (P < 0.001) in group 1, plus the higher fat content of the two remaining groups, are evidence of the higher fatness of carcasses in groups 2 and 3. The fat tissues except the subcutaneous fat were significantly related with the leptin concentrations at slaughter. The leptin concentration of lambs slaughtered at 30 kg live weight surpassed significantly the values noted in groups 1 and 2 (P < 0.001). The correlations between leptin and body composition indicate that plasma leptin concentration at 30 kg live weight can be a predictor of body fat. The correlation of meat weight with leptin concentration has shown no statistical differences.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".