Quantitative Analysis of the Relationship between Ruminal Redox Potential and pH in Dairy Cattle: Influence of Dietary Characteristics
Bibliographic record
Abstract
The ruminal redox potential (Eh) can reflect the microbiological activity and dynamics of fermentation in the rumen. It might be an important indicator of rumen fermentation in combination with pH. However, the ruminal Eh has been rarely studied in dairy cows due to the difficulty of its measurement, and the relationship between ruminal Eh and pH is not clear. The objective of this study was to investigate the relationship between ruminal Eh and pH of dairy cows by meta-analysis of systematic measurements from different experiments. A database was constructed from 22 experiments on cannulated dairy cattle including 57 dietary treatments. The ruminal pH and Eh were measured without air contact between 0 and 8 h post-feeding. The results demonstrated a quadratic correlation between ruminal Eh and pH with a reliable within-animal variation (Eh = -1697 + 540.7 pH -47.7 pH2, nobservation = 70, nanimal = 26, P Eh, but not always to the same extent. Some of them still influenced the relationship between ruminal Eh and pH. While the mechanism of the interaction between ruminal Eh and pH remains to be elucidated, it would be interesting to associate Eh to microbial profile, ruminal VFA concentration and milk production performance in future studies.
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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 | 0.011 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".