Greenhouse gas emissions of Canadian beef production in 1981 as compared with 2011
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The present study compared the greenhouse gas (GHG) emissions, and breeding herd and land requirements of Canadian beef production in 1981 and 2011. In the analysis, temporal and regional differences in feed types, feeding systems, cattle categories, average daily gains and carcass weights were considered. Emissions were estimated using life-cycle assessment (cradle to farm gate), based primarily on Holos, a Canadian whole-farm emissions model. In 2011, beef production in Canada required only 71% of the breeding herd (i.e. cows, bulls, calves and replacement heifers) and 76% of the land needed to produce the same amount of liveweight for slaughter as in 1981. Compared with 1981, in 2011 the same amount of slaughter weight was produced, with a 14% decline in CH4 emissions, 15% decline in N2O emissions and a 12% decline in CO2 emissions from fossil fuel use. Enteric CH4 production accounted for 73% of total GHG emissions in both years. The estimated intensity of GHG emissions per kilogram of liveweight that left the farm was 14.0 kg CO2 equivalents for 1981 and 12.0 kg CO2 equivalents for 2011, a decline of 14%. A significant reduction in GHG intensity over the past three decades occurred as a result of increased average daily gain and slaughter weight, improved reproductive efficiency, reduced time to slaughter, increased crop yields and a shift towards high-grain diets that enabled cattle to be marketed at an earlier age. Future studies are necessary to examine the impact of beef production on other sustainability metrics, including water use, air quality, biodiversity and provision of ecosystems services.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it