Truly Absorbed Microbial Protein Synthesis, Rumen Bypass Protein, Endogenous Protein, and Total Metabolizable Protein from Starchy and Protein-Rich Raw Materials: Model Comparison and Predictions
Bibliographic record
Abstract
This study was carried out to measure truly absorbed microbial protein synthesis, rumen bypass protein, and endogenous protein loss, as well as total metabolizable protein, from starchy and protein-rich raw feed materials with model comparisons. Predictions by the DVE2010 system as a more mechanistic model were compared with those of two other models, DVE1994 and NRC-2001, that are frequently used in common international feeding practice. DVE1994 predictions for intestinally digestible rumen undegradable protein (ARUP) for starchy concentrates were higher (27 vs 18 g/kg DM, p < 0.05, SEM = 1.2) than predictions by the NRC-2001, whereas there was no difference in predictions for ARUP from protein concentrates among the three models. DVE2010 and NRC-2001 had highest estimations of intestinally digestible microbial protein for starchy (92 g/kg DM in DVE2010 vs 46 g/kg DM in NRC-2001 and 67 g/kg DM in DVE1994, p < 0.05 SEM = 4) and protein concentrates (69 g/kg DM in NRC-2001 vs 31 g/kg DM in DVE1994 and 49 g/kg DM in DVE2010, p < 0.05 SEM = 4), respectively. Potential protein supplies predicted by tested models from starchy and protein concentrates are widely different, and comparable direct measurements are needed to evaluate the actual ability of different models to predict the potential protein supply to dairy cows from different feedstuffs.
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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".