Long-term trends in greenhouse gas emissions from the Canadian poultry industry
Bibliographic record
Abstract
As people become more aware of the environmental footprint of different foods, consumers may modify their diets to reduce the impact of their diets on the environment. For this to occur, it is necessary to know the impact that individual food types have on the environment. This publication presents the greenhouse gas (GHG) emissions as well as the GHG emission intensity associated with various types of poultry production in Canada for the census years 1981 to 2006. Greenhouse gas emissions were calculated using the methodology from the Intergovernmental Panel on Climate Change adjusted for conditions in Canada. Direct emissions of CH4, N2 O, and CO2 from birds, their facilities, and the avian crop complex, corresponding to the area used to grow the crops that feed Canadian poultry, were estimated using poultry diet surveys. Between 1981 and 2006, because of the strong growth of broiler production, GHG emissions from the poultry industry increased by 40%. The main GHG was N2 O, representing approximately 57% of the total emissions. Fossil fuel CO2 accounted for approximately 38%, whereas CH4 accounted for 5%. In western Canada, GHG emission intensities decreased owing to a reduction in the consumption of fossil fuels associated with the adoption of reduced- and no-tillage cropping systems, whereas in eastern Canada, the reduction was due to lower N2 O emissions. The emissions of all 3 GHG from turkeys decreased because of the more rapid turnover of a marketable product (shortened life span) in later census years. Compared with other Canadian meat protein commodities in 2001, poultry emitted only 47% as much GHG per unit of live weight as pork and only 10% as much GHG per unit of live weight as beef.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".