Modelling monthly NH3 emissions from dairy in 12 Ecoregions of Canada
Bibliographic record
Abstract
Sheppard, S. C., Bittman, S., Swift, M. L. and Tait, J. 2011. Modelling monthly NH 3 emissions from dairy in 12 Ecoregions of Canada. Can. J. Anim. Sci. 91: 649-661. Ammonia (NH3) from livestock manure is emitted from barns, storages and manured land, and is a loss to the farm operations, while atmospheric NH3 has potential impacts beyond the farm, including human health and ecological damage. Models are used to estimate the intensity and spatial extent of NH3 emissions, and this paper reports a recent model developed for quantifying emissions from the dairy sector in Canada. The estimated overall average emission to the atmosphere in Canada in 2006 was 42.4±9.0 kg NH3 cow-1 yr-1 from a lactating cow, and total emission from the Canadian dairy sector was 56000 t NH3. On many farms the NH3 emissions may have been a significant portion of the N requirements of their crops. The emission estimates in the 12 Ecoregions were proportional to the animal census. Emissions generally peaked in May, mainly because of landspreading of manure. There were also differences in emissions per animal among the Ecoregions related to the specific practices, such as amount of grazing and injection of slurry. The sensitivity analysis suggested that a shift from the present 14% injection of slurry manure into soil to 80% may be effective overall, potentially decreasing annual emissions by 13% and emissions in May by 27%.
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.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".