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Record W1799146555 · doi:10.4141/cjas2010-005

Modelling monthly NH<sub>3</sub> emissions from dairy in 12 Ecoregions of Canada

2011· article· en· W1799146555 on OpenAlexaffvenueabout
Steve Sheppard, Shabtai Bittman, Mark Swift, J. Tait

Bibliographic record

VenueCanadian Journal of Animal Science · 2011
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsAgriculture Food and Rural DevelopmentAgriculture and Agri-Food Canada
Fundersnot available
KeywordsManureEnvironmental scienceLivestockSlurryManure managementGrazingAnimal wasteDairy cattleAnimal scienceAtmospheric sciencesGeographyEnvironmental engineeringAgronomyForestryBiologyWaste management

Abstract

fetched live from OpenAlex

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 (NH 3 ) from livestock manure is emitted from barns, storages and manured land, and is a loss to the farm operations, while atmospheric NH 3 has potential impacts beyond the farm, including human health and ecological damage. Models are used to estimate the intensity and spatial extent of NH 3 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 NH 3 cow −1 yr −1 from a lactating cow, and total emission from the Canadian dairy sector was 56000 t NH 3 . On many farms the NH 3 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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.033
GPT teacher head0.201
Teacher spread0.168 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2011
Admission routes3
Has abstractyes

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