Effect of Dietary Fiber on Endogenous Nitrogen Flows in Lactating Dairy Cows
Bibliographic record
Abstract
The effect of dietary fiber on endogenous N secretion was studied using a 15N isotope dilution technique in four fistulated Holstein cows. Two isonitrogenous diets differing only in fiber (NDF and ADF) content were used in a crossover design. One diet (HF) contained 37.4% NDF, while the other (LF) contained 23.3%. A new model was developed to estimate endogenous N secretions and losses for the preintestinal, intestinal, and the total sections of the gastrointestinal tract. Three precursor pools: TCA-soluble fraction of plasma, intestinal mucosa, and milk were compared. Although endogenous losses estimated with the model were numerically different for each precursor pool selected (TCA-soluble fraction > mucosa > milk), treatment effects were similar. As intestinal mucosa is probably closest to the precursor pool, these data are discussed. Non-urea N endogenous secretions contributed 13% of the duodenal N flow but were not affected by the fiber content of the diet. The nonurea N endogenous flow at the duodenum was comprised of approximately equal inputs from endogenous N direct, and that incorporated into the microbial biomass. Total endogenous N flows at the duodenum exceeded, by nearly twofold, estimated inputs of urea-N to microbial biomass. Metabolic fecal output averaged 17% of fecal N and was not affected by level of dietary fiber, but net losses from secretions occurring in the small intestine were higher with the low fiber diet. Overall, endogenous N secretions represented 30% of total digestive tract protein synthesis.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".