Variation among individual dairy cows in methane measurements made on farm during milking
Bibliographic record
Abstract
The objective of this study was to quantify on-farm variation between and within cows in methane emissions measured during milking, and to determine which factors are related to this variation. Methane emission rate during milking (MERm) was recorded at milking using methane analyzers installed in automatic (robotic) milking stations for 215 cows over a period of 5 mo. Between-cow variation in MERm (mean 2.07, SD 0.629 g/min), was greater than within-cow variation and was related to variation in body weight, milk yield, parity, and week of lactation. Estimation of daily methane emissions from MERm data, using an equation derived from comparisons with respiration chamber data, produced estimates that ranged from 278 to 456 g of CH₄/d and were commensurate with values predicted from metabolizable energy requirements for observed body weight and milk yield. It is concluded that methane emissions vary considerably between dairy cows housed under commercial conditions. This variation needs to be taken into account when performing inventories or testing mitigation strategies, but it might offer opportunities for genetic selection.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".