Including essential oils in lactating dairy cow diets: effects on methane emissions1
Bibliographic record
Abstract
The objective of this study was to examine the effects of dietary supplementation of garlic and juniper berry essential oils on methane (CH4) and carbon dioxide (CO2) emissions from lactating dairy cows. Four ruminally cannulated, lactating Holstein cows were used in a 4 × 4 Latin square (21-day period; 11 days of adaptation). Cows were fed a total mixed ration (60 : 40 forage : concentrate ratio) without supplementation (no additive; negative control) or supplemented with monensin (330 mg/day; positive control), garlic oil (5 g/day) or juniper berry oil (2 g/day). Methane and CO2 emissions were measured using the sulfur hexafluoride tracer technique. Dietary supplementation of lactating cows with juniper berry oil or garlic oil did not affect (P > 0.05) CH4 or CO2 production, whether expressed as g/day, g/kg DMI, g/kg milk or as g/kg DMI/BW0.75. At the doses administered in this study, the anti-methanogenic effect of garlic and juniper berry oils previously observed in vitro were not confirmed in vivo.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".