Farm practices as they affect NH3 emissions from beef cattle
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
Sheppard, S. C. and Bittman, S. 2012. Farm practices as they affect NH 3 emissions from beef cattle. Can. J. Anim. Sci. 92: 525-543. Beef cattle farms in Canada are very diverse, both in size and management. Because the total biomass of beef cattle in Canada is larger than any other livestock sector, beef also has the potential for the largest environmental impact. In this study we estimate NH3 emissions associated with beef cattle production across Canada using data on farm practices obtained from a detailed survey answered by 1380 beef farmers in 11 Ecoregions. The farms were various combinations of cow/calf, backgrounding and finishing operations. The proportion of animals on pasture varied markedly among Ecoregions, especially for cows and calves, and this markedly affected the estimated NH3 emissions. The crop components of feed also varied among Ecoregions, but the resulting crude protein concentrations were quite consistent for both backgrounding and finishing cattle. Manure was stored longer in the west than in the east, and fall spreading of manure was notably more common in the west, especially when spread on tilled land. The estimated NH3 emissions per animal were relatively consistent across Ecoregions for confinement production, but because the proportion of animals on pasture varied with Ecoregion, so did the overall estimated NH3 emissions per animal. Temperature is a key factor causing Ecoregion differences, although husbandry and manure management practices are also important. Hypothetical best management practices had little ability to reduce overall emission estimates, and could not be implemented without detailed cost/benefit analysis.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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