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Record W3025349723 · doi:10.1139/cjss2013-008

Alternative transformations of nitrous oxide soil flux data to normal distributions

2014· article· en· W3025349723 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBioOne Complete (BioOne) · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil Geostatistics and Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsLog-normal distributionNitrous oxideNormal distributionMathematicsStatisticsTransformation (genetics)NormalityFlux (metallurgy)QuantileVariance (accounting)Distribution (mathematics)Soil scienceEnvironmental scienceChemistryMathematical analysisBiologyEcology

Abstract

fetched live from OpenAlex

Moulin, A. P., Glenn, A., Tenuta, M., Lobb, D. A., Dunmola, A. S. and Yapa, P. 2014. Alternative transformations of nitrous oxide soil flux data to normal distributions. Can. J. Soil Sci. 94: 105-108. Non-normal distributions of soil N2O fluxes are commonly log transformed prior to statistical analysis. These data are transformed to ensure that analysis of variance and regression based on least squares, meet the assumptions of normality for the distribution of data and equality of variances. Analysis of micrometeorological and static chamber-based fluxes of N2O in Manitoba show that continuous functions such as the Johnson Su and Sl, Generalized Log or normal quantile may be useful as alternatives to the lognormal, which was relatively less effective in transforming data, though each transformation should be evaluated on a case-by-case basis.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.592
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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.233
GPT teacher head0.257
Teacher spread0.024 · 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