Supplying standardized ileal digestible lysine via soybean meal below estimated requirements for late gestating gilts does not negatively affect mammary development
Bibliographic record
Abstract
Forty-eight Yorkshire × Landrace gilts were used to determine whether supplying lysine via soybean meal below estimated requirements influences mammary development in late gestation. Gilts were assigned one of three isocaloric (2505 kcal/kg net energy) diets on gestation day 90: (1) control (CON; 18.38% crude protein (CP); 18.2 g/day standardized ileal digestible (SID) Lys, being near NRC (2012) estimated requirements; n = 16), or diets that provided SID Lys below estimated requirements with Lys supplied primarily by soybean meal: SBM1 (14.69% CP; 12.4 g SID Lys/day; n = 16) or SBM2 (17.81% CP; 14.6 g SID Lys/day; n = 16). Mammary development was assessed on gestation day 110. Gilt body weight and backfat depth gain between gestation days 90 and 110 were not influenced by dietary treatment ( P > 0.10). Moreover, mammary parenchymal and extraparenchymal tissue masses, as well as protein and fat contents and concentrations of DNA and RNA in parenchymal tissue were not influenced by dietary treatment ( P > 0.10). Therefore, providing Lys up to 34% below estimated requirements via soybean meal in late gestation had no immediate detrimental effect on mammary development.
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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".