Diurnal and Seasonal Patterns of Methane Emissions from a Dairy Operation in North China Plain
Bibliographic record
Abstract
In China, dairy cattle managed in collective feedlots contribute about 30% of the milk production and are believed to be an important contributor to national methane emissions. Methane emissions from a collective dairy feedlot in North China Plain (NCP) were measured during the winter, spring, summer, and fall seasons with open-path lasers in combination with an inverse dispersion technique. Methane emissions from the selected dairy feedlot were characterized by an apparent diurnal pattern with three peaks corresponding to the schedule of feeding activities. On a per capita basis, daily methane emission rates of these four seasons were 0.28, 0.32, 0.33, and 0.30 kg head −1 d −1 , respectively. In summary, annual methane emission rate was 112.4 kg head −1 yr −1 associated with methane emission intensity of 32.65 L CH 4 L −1 of milk and potential methane conversion factor Y m of 6.66% of gross energy intake for mature dairy cows in North China Plain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 teacher head, 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".