The soybean oil equivalency of soybean meal indicates a high energy value of soybean meal when fed to growing pigs
Bibliographic record
Abstract
An experiment was conducted to test the hypothesis that the energy in soybean meal (SBM) fed to pigs determined using a fat equivalency procedure is greater than current book values for net energy (NE). A total of 120 growing pigs were allotted to five dietary treatments. A diet based on corn, soy protein concentrate (SPC), and synthetic cellulose and three diets containing 2%, 4%, or 6% soybean oil (SBO) were formulated. A fifth diet that contained corn, SPC, and 12% SBM, but no SBO, was also formulated. Pigs were fed experimental diets for four weeks and daily gain, daily fed intake, and gain-to-feed ratio (G:F) were calculated. Regression of G:F for pigs fed diets without SBM against the increasing levels of SBO was used to create an equation to predict the response in G:F of adding SBO to the diets. Results demonstrated that G:F increased (linear, P < 0.001) by increasing SBO in the diets and the G:F of pigs fed the diet containing 12% SBM corresponded to a diet containing 4.70% SBO, which is equivalent to 2955 kcal NE per kg. In conclusion, the NE of SBM in diets for pigs is greater than previously thought.
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 | 0.000 |
| 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".