Quantifying ruminal digestion of organic matter and neutral detergent fiber using the omasal sampling technique in cattle—A meta-analysis
Bibliographic record
Abstract
A data set from 32 studies (122 diets) was used to evaluate the accuracy and precision of the omasal sampling technique by investigating the relationships between ruminal and total digestion of neutral detergent fiber (NDF), between intake and apparent and true ruminal digestion of organic matter (OM), and between omasal NAN flow and milk protein yield. A mixed model regression analysis with random study effect was used to evaluate the relationships. The data were obtained when feeding North American diets (n=36) based on alfalfa silage, corn silage, and corn grain and North European diets (n=86) comprising grass silage supplemented with barley-based concentrates. In all studies, digesta flow was quantified using a triple-marker approach. Standard deviations of ruminal NDF and true OM digestibility were smaller than typically reported in duodenal sampling studies using only chromic oxide as a flow marker. The relationship between total and ruminal NDF digestion was consistent, indicating little variation in the proportion of total-tract NDF digestion that occurred in the rumen. Furthermore, the slope of this regression indicated that 94.7% (+/-2.7%) of total NDF digestion occurred in the rumen. The slopes of mixed model regression equations between OM intake and amount digested indicated that 42% (+/-2.4%) and 74% (+/-3.1%) of OM was apparently and truly digested in the rumen, respectively. The contribution of the rumen to total-tract apparent OM digestion was 62% (+/-2.6%). The close relationship between omasal flow of nonammonia crude protein and milk protein yield (with adjusted residual mean squared error=31 g) provided further confidence in the reliability of omasal flow measurements.
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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 | 0.030 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.035 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".