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Record W2592363366 · doi:10.1139/cjss10070

Probability distribution functions for short-term daily nitrous oxide fluxes in a prairie pothole agricultural landscape in western Canada

2011· article· en· W2592363366 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBioOne Complete (BioOne) · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil Geostatistics and Mapping
Canadian institutionsUniversity of ManitobaAgriculture and Agri-Food Canada
Fundersnot available
KeywordsEnvironmental scienceLog-normal distributionProbability distributionProbability density functionHydrology (agriculture)Physical geographyStatisticsGeographyMathematicsGeology

Abstract

fetched live from OpenAlex

Moulin, A., Tenuta, M., Lobb, D., Dunmola, A. and Yapa, P. 2011. Probability distribution functions for short-term daily nitrous oxide fluxes in a prairie pothole agricultural landscape in western Canada. Can. J. Soil Sci. 91: 303-307. Probability distributions of N2O fluxes are often non-normal due to large temporal and spatial variability of environmental factors. The most common approaches to statistical analyses of these fluxes in the scientific literature are to transform data with a log function, or conduct non-parametric tests. Analysis of N2O flux data for 128 sites within a 16-ha field, taken on 20 dates in 2005 and 2006 near Brandon, Manitoba, show that the Johnson Su and generalized log probability distributions provided the best fit for the majority of sample dates. The results of this research indicate that statistical analysis of N2O fluxes with the Johnson Su probability function should be considered as an alternative to the lognormal function.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.749

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)0.0000.000

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 head0.192
GPT teacher head0.220
Teacher spread0.027 · 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