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Record W3088418240 · doi:10.4231/dfb0-f030

Nitrous oxide emissions and field-level nitrogen balance of maize and other field crops: Data for meta-analysis

2020· article· en· W3088418240 on OpenAlexaff
Alison J. Eagle, Sylvie M. Brouder, G. S. Cambareri, C. F. Drury, Timothy B. Parkin, Douglas R. Smith, G. Philip Robertson, Rodney T. Venterea, Claudia Wagner‐Riddle, Cameron M. Pittelkow, Rex A. Omonode, Tony J. Vyn, David E. Pelster, Martin H. Chantigny

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsUniversity of GuelphAgriculture and Agri-Food Canada
Fundersnot available
KeywordsField cropEnvironmental scienceAgronomyNitrous oxideField (mathematics)NitrogenBalance (ability)ChemistryMathematicsBiology

Abstract

fetched live from OpenAlex

<p>This is a compilation of field research data measuring nitrous oxide emissions from 55 different field crop experiments reported in 66 different publications. The data are mostly maize in the Corn Belt, but also include other crops and regions around the globe. All studies reported crop yield as well as N<sub>2</sub>O losses. Experiment dates range from 1993 to 2017. Map illustrates observations for which multiple non-zero N rates were monitored -- this is the restricted dataset used to determine the generalized relationship between N<sub>2</sub>O and N balance (where N balance is N inputs minus N removed). The dataset includes a total of 805 separate site-treatment-year observations, with up to 87 different variables for each observation.</p> <p>This dataset contains yearly management, production, and N<sub>2</sub>O emission outcomes - along with other explanatory variables - drawn from temperate-region field crop experiments. Data subsets include: 1) maize in the North American Corn Belt on silt loam soils as published previously by McLellan et al. 2018, 2) additional observations for maize in the Corn Belt on silt loam soils, 3) maize in the Corn Belt grown on soils of other texture classes, 4) maize in the Corn Belt fertilized with livestock manure, and 5) other crops and regions. Yearly observations are averages of 3-4 replicates for each treatment-site, with measurement variability included where available. Most observations and explanatory variables originate from published data in peer-reviewed publications; some gaps were filled with data provided by field researchers, and weather and soil data gaps were filled using publicly available datasets.</p> <p>The data are used in the following publication:</p> <p>Eagle, A. J., McLellan, E. L., Brawner, E. M., Chantigny, M. H., Davidson, E. A., Dickey, J. B., et al. (2020). Quantifying on‐farm nitrous oxide emission reductions in food supply chains. <em>Earth's Future</em>, 8, e2020EF001504. https://doi.org/10.1029/ 2020EF001504</p>

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.195
Threshold uncertainty score1.000

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.228
GPT teacher head0.307
Teacher spread0.080 · 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.

Study designObservational
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

Citations0
Published2020
Admission routes1
Has abstractyes

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