In vitro N degradability and N digestibility of raw, roasted or extruded canola, linseed and soybean
Bibliographic record
Abstract
The N degradability and N digestibility of raw, roasted or extruded oilseeds were studied using an in vitro enzyme method. The N degradability and N digestibility of canola, linseed and soybean were calculated based on the proportional difference in N remaining after incubation and the initial N content. Heat treatments increased the undegradable N fraction of linseed and soybean, whereas that of canola was decreased by extrusion. Heat treatments did not decrease the N digestibility of the oilseeds compared to raw samples. The high N digestibility and lower acid detergent insoluble N values of heat treated oilseeds indicated no indigestible complexes were formed. In conclusion, roasting or extrusion can be used to increase the undegradable N fraction of linseed and soybean to increase the dietary protein availability for digestion in ruminants, but was less effective for canola. The present heat treatments did not damage the protein or affect the N digestibility of the oilseeds.;
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) | 0.001 | 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".