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Record W2063891087 · doi:10.1155/2011/190234

Diurnal and Seasonal Patterns of Methane Emissions from a Dairy Operation in North China Plain

2011· article· en· W2063891087 on OpenAlexafffund
Zhiling Gao, Huijun Yuan, Wenqi Ma, Jianguo Li, Xuejun Liu, R. L. Desjardins

Bibliographic record

VenueAdvances in Meteorology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsAgriculture and Agri-Food Canada
FundersBundesministerium für Bildung und ForschungAgriculture and Agri-Food CanadaNational Natural Science Foundation of China
KeywordsMethaneEnvironmental scienceChinaFeedlotAnimal sciencePer capitaAtmospheric methaneGeographyAtmospheric sciencesForestryEcologyBiologyPopulationPhysicsDemography

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.007
GPT teacher head0.219
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2011
Admission routes2
Has abstractyes

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