Methane emissions from feedlot cattle in Australia and Canada
Bibliographic record
Abstract
Raising beef cattle in open feedlots is a well established practice in Canada and is gaining acceptance in Australia because it results in more consistent meat quality. These facilities are regional ‘hot spots’ of methane (CH4) emissions, resulting from the high stocking density and the large amount of fermentation occurring in the rumen (enteric CH4). Our objective was to compare CH4 emissions from a typical feedlot in Australia (Queensland) and in Canada (Alberta) and also to compare these against modelled emissions. Methane concentration and wind data were monitored over a portion of each feedlot and a dispersion model was used to calculate CH4 emissions during a summer period. The average CH4 emission was 166 ± 90 and 214 ± 61 g/animal.day for the feedlot in Queensland and in Alberta, respectively. The lower CH4 emission at the Queensland feedlot was attributed to the lighter weight of the cattle, and consequently their lower intake, and supplementation of the diet with lipids. The lipid effect on CH4 emissions is also speculated to cause some models to overestimate the measured CH4 emissions. A lower CH4 emission also occurred during daylight hours at the Queensland feedlot and was attributed in part to heat stress as defined by the temperature–humidity index.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".