Enteric Methane Emissions and Mitigation Opportunities for Canadian Cattle Production Systems. otherareas/pdf/CcbMethaneemmissionsWittenburg.pdf> (accessed
Bibliographic record
Abstract
Methane (CH4) is a colorless, odorless gas generated as a by-product of microbial fermentation of feed in the gastrointestinal tract of ruminant animals. Methane producing bacteria, commonly referred to as methanogens, use the hydrogen and carbon dioxide produced as end products of microbial digestion to generate energy for growth, with CH4 as an end product. Canadian estimates for enteric CH4 emissions from ruminant animals show a 10.6 % increase from 1990 to 2000; 15,994 vs 17,696 kt carbon dioxide (CO2) equivalents/yr respectively. As 1 g CH4 is equivalent to 55.2 kJ of lost feed energy, mitigation strategies can result in improved feed utilization as well as contribute to Canada’s commitment to reduce GHG emissions. Data collected from Canadian research indicate that energy losses associated with enteric CH4 emissions range from 2 to 11.3 % of gross energy intake. Numerous mitigation strategies have been suggested in the literature, including: manipulation of rumen microfloral populations, diet manipulation to provide alternate hydrogen acceptors, diet manipulation to shift the fermentation pathway, management for improved productivity, and genetic selection for low methane emitting animals. Results from Canadian trials show that there are opportunities to reduce enteric methane emissions in commercial production systems. Many of these mitigation strategies will influence carbon sequestration opportunities and
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.042 | 0.003 |
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".