253 The Effect of Increasing Standardized Ileal Digestible Methionine Intake on Whole-Body Nitrogen Retention of Gilts During Late Gestation
Bibliographic record
Abstract
Abstract A total of 70 gestating gilts (166±13 kg BW) were used to determine whole-body N retention when standardized ileal digestible (SID) methionine (Met) was fed at one of seven levels (n=10), ranging between 50 and 150% of estimated requirements during late gestation. The experimental diets provided excess Cys and 2.61, 3.39, 4.44, 5.22, 6.00, 7.05, and 7.83 g SID Met/d, respectively, with a feed allowance of 2.61 kg/d. Diets were fed to individual gilts for a 7-d adaptation period followed by a N balance period between gestation days 109 and 112. Contrast statements were used to determine linear and quadratic effects of the dietary inclusion level of Met. The average N intake was 70.8 g/d among treatments. Urinary N excretion decreased with increasing SID Met content, with no further change after 3.39 g/d SID Met (quadratic; P < 0.0001). Fecal N excretion decreased with increasing SID Met content, with no further change after 5.22 g/d SID Met (linear and quadratic; P < 0.0001 and P < 0.05, respectively). Whole-body N retention increased as SID Met content increased between 2.61 and 4.44 g/d SID Met, no differences were observed between 4.44 and 7.05 g/d SID Met, with intermediate N retention for gilts fed 7.83 g/d SID Met (linear and quadratic; P < 0.01 and P < 0.0001). Whole-body N retention efficiency (% of intake) was greatest (60.74%) at 7.05 g/d SID Met. Whole-body N retention (g/d) was optimized at 4.04 and 4.58 g/d SID Met based on linear and quadratic broken-line linear models, respectively, for gilts during late gestation. Therefore, for whole-body protein retention, the average SID Met requirements (4.31 g/d) appear to be less versus those recommended by the NRC in late gestation (5.22 g SID Met/day), which do not take into consideration the non-protein partitioning of dietary Met.
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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 | 0.000 | 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) | 0.001 | 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".