Comparison of Techniques for Measurement of Rumen pH in Lactating Dairy Cows
Bibliographic record
Abstract
Subacute rumen acidosis is thought to be a common condition in early lactating dairy cattle; however, diagnosis is difficult. There are currently only two techniques available for measuring rumen pH under field conditions: rumenocentesis and oral stomach tube. Sixteen rumen-fistulated cows were sampled in four sites of the rumen (cranial-ventral, caudal-ventral, central, and cranial-dorsal) with a rumen cannula. Rumen pH results were compared to those obtained at the same time with rumenocentesis and with an oro-ruminal (Geishauser) probe. Rumen fluid was obtained between 6 and 12 wk of lactation. Samples were analyzed for pH, lactate, bicarbonate, sodium, potassium, and chloride. Rumen pH results were also compared to those obtained from 24-h continuous rumen pH measurement using indwelling rumen pH probes. Oro-ruminal probe samples had the highest pH values and the highest bicarbonate concentrations. Rumenocentesis samples had the lowest pH values and the lowest bicarbonate concentrations. Small differences in electrolyte concentrations were noted among rumen fluid collection techniques in the different rumen sites. The highest correlations of rumen pH were obtained between rumenocentesis and rumen cannulation (cranial-ventral), and between rumen cannulation (cranial-ventral) and the 24-h indwelling pH meter. Compared with samples obtained from the cranial-ventral rumen, rumenocentesis was more sensitive than the oro-ruminal probe in the measurement of low rumen pH; both techniques were moderately specific. The most accurate field technique was rumenocentesis. Improved field techniques are required for better on-farm diagnosis of subacute rumen acidosis.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".