PSVII-12 The effect of feeding a LucraFit® nursery program without lactose on piglet performance
Bibliographic record
Abstract
Abstract Four hundred forty weaned pigs, initial weight of 5.86 kg and 21 days of age, were used to evaluate the effect of feeding a LucraFit® nursery program on piglet performance. Pigs were randomly assigned to one of two treatments Control or LucraFit® with 12 replicates per treatment and 20 pigs per pen. Pigs were fed a four-phase nursery feed budget of 1.13, 2.27, 5.44, and 20.64 kg/pig for phases 1–4, respectively. Control diets contained 18% lactose in phase 1 and 0% in phase 2, 3, and 4. LucraFit® diets contained 0% lactose and LucraFit® was added at 2.5, 2.5, 1.25% in phase 1, 2 and 3, respectively. Body weights were taken on day 0, 8, 15, 22, 29, 36, and 43 with corresponding ADG, ADFI, G:F calculated. Data were analyzed using the Mixed procedure of SAS with pen as experimental unit. Period 1 (d0 to 8) ADG tended to increase (P < 0.10;0.188 vs 0.175 kg/d) and G:F increased (P < 0.05;1.38 vs 1.06) in the LucraFit® treatment. Period 1 ADFI was greater (P < 0.05) for the Control treatment (0.166 vs 0.141 kg/d). Period 2 (d8 to d 15), LucraFit® treatment tended (P < 0.10) to increase ADG (0.416 vs 0.398 kg/d) and increased (P < 0.05) G:F (0.973 vs 0.894). Period 3 (d15 to d 22), ADFI was increased (P < 0.05) with LucraFit® treatment (0.628 vs 0.577 kg/d) and therefore increased (P < 0.05) G:F for Control treatment (0.794 vs 0.752. Period 6 (d36 to d 43), LucraFit® treatment increased (P < 0.05) ADG (1.57 vs 1.40 kg/d) and G:F (0.565 vs 0.500). Overall (d0 to 43) Gain:Feed was increased (P < 0.05) with LucraFit® treatment (0.713 vs 0.691). Final nursery body weight (d 43) tended (P = 0.08) to increase with LucraFit® treatment (27.05 vs 26.32). The results of this study suggest that feeding LucraFit® in lactose free nursery diets improves feed efficiency.
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) | 0.001 | 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) | 0.003 | 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".