Probability distribution functions for short-term daily nitrous oxide fluxes in a prairie pothole agricultural landscape in western Canada
Bibliographic record
Abstract
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 N 2 O 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 N 2 O 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 N 2 O fluxes with the Johnson Su probability function should be considered as an alternative to the lognormal function.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".