Determination of Methane Emissions from a Dairy Feedlot Using an Inverse Dispersion Technique
Bibliographic record
Abstract
Methane emission from dairy feedlot in China is one important source of global methane budget due to the large global warming potential(a factor of 25 in comparison with CO2).To indicate methane emission patterns on dairy feedlot in North China,a combination of an inverse dispersion technique and open-path laser was used to quantify patterns of methane emissions on a dairy feedlot(Baoding,Hebei)during winter and spring seasons.During these two measurement seasons,the total animal herd was 1 200 heads in average.Results showed that both in winter and spring seasons,methane emissions from the selected dairy feedlot were characterized with a apparent diurnal pattern,that was,the emission peaks occurred at 05:00,11:30 and 16:30,respectively,which was generally in agreement with the schedule of feeding activities;it also indicated that total daily emission rate of methane including enteric formation and manure storage within feedlot during winter and spring seasons were 0.31 t·d-1 and 0.36 t·d-1,and on the per capita base including total animal herd,methane emission rates were 0.26 t·d-1 and 0.30 kg·d-1,where methane emission rate during spring season was about 16.7 greater than winter season,thus a relatively large seasonal difference on methane emission rates was identified.
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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) | 0.000 | 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 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".