Modeling nutrient supply to dairy cattle from a feedstuff using NRC-2001 (a TDN-based model) with inputs based on in situ and mobile bag technique measurements
Bibliographic record
Abstract
The objectives of this study were to use the NRC-2001 model with inputs based on in situ and mobile bag techniques to (1) predict the potential nutrient supply to dairy cows using an exampled feed- whole lupin seeds that were systematically toasted and (2) quantitatively determine the effects of toasting (which shifted degradation of protein from the rumen to the abomasum and small intestine without changing intestinal digestion) and optimal toasting conditions by the NRC-2001 model. The quantitative predictions were made in terms of: (1) rumen undegraded and degraded feed protein, (2) truly absorbed undegraded protein, (3) potential microbial protein synthesized in the rumen from rumen available protein or (4) from total digestible nutrients (TDN), (5) truly absorbed rumen synthesized microbial protein, (6) truly absorbed rumen endogenous protein, (7) total metabolizable protein (MP), as well as (8) the protein degradation balance (PDB). The results show that using the NRC-2001 model with inputs based on in situ and mobile bag techniques, the predicted PDB and MP supply to dairy cattle was significantly improved. However, no optimal condition could be obtained from this study due to high PDB values (>48 g kg-1 DM) in all the treatments, predicted by the model. With toasting, temperature and/or duration could go still higher than 136°C and/or longer than 15 min to further prevent potential N loss in the rumen if total tract digestion is not depressed. More study is needed. However, the results differed from that published with the DVE/OEB system (a non-TDN-based model) although the two models had significant correlations with high R (>0.99) values. Using the NRC model, the overall mean for MP was higher (+10 g kg-1 DM), but the PDB values were lower (-12 g kg-1 DM) in comparison with that predicted by the non-TDN based model for the whole lupin seeds. Key words: Modeling nutrient supply, dairy cattle; National Research Council, in situ, mobile bag technique
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".