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Record W2058156493 · doi:10.1080/10440046.2010.493376

The Protein-based GHG Emission Intensity for Livestock Products in Canada

2010· article· en· W2058156493 on OpenAlexaffabout
J.A. Dyer, X.P.C. Vergé, R. L. Desjardins, Devon E. Worth

Bibliographic record

VenueJournal of Sustainable Agriculture · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsLivestockEmission intensityEnvironmental scienceGreenhouse gasIntensity (physics)Agricultural economicsBusinessNatural resource economicsAgricultural scienceEnvironmental protectionChemistryGeographyEconomicsEcologyBiologyForestryPhysics

Abstract

fetched live from OpenAlex

Assessments of the total greenhouse gas (GHG) emissions and emission intensities had been carried out prior to this analysis for dairy, beef, pork, and poultry in Canada. The GHG emission intensities of these industries were based on different units of food produced. In this paper, the GHG emission intensities of the four livestock industries were compared on the basis of the weight of protein produced. The protein-based emission intensity for beef was almost four times as high as the GHG emission intensity for milk production. The emission intensities of pork production were lower than the emissions from milk production because of lower CH4 emissions. Broilers had the lowest GHG emission intensity of all five livestock commodities. The next lowest GHG intensity was for egg production. The differences between the egg and broiler intensities cannot be attributed to any one GHG. The number of breeding animals that must be maintained in order to produce one animal for slaughter is much higher for cattle than...

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.859

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.003
GPT teacher head0.176
Teacher spread0.173 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations63
Published2010
Admission routes2
Has abstractyes

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