Probability Distribution and Spatial Dependence of Nitrous Oxide Emission
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.
Bibliographic record
Abstract
Climate controls soil N 2 O emissions via its effects on soil properties such as water‐filled pore space. Changes in climate should produce changes in the probability distribution and spatial dependency of soil N 2 O data. Knowing the extent of the changes in the distribution of this data is important for validating model predictions. The objectives of this study were to describe the probability distributions and estimate the spatial dependency of soil N 2 O emission data. On a hummocky, agricultural landscape in Saskatchewan, N 2 O emission data and related soil variables were taken from a 128‐point transect 15 times over 2 yr. Probability distributions were compared using a Chi‐square test. The range in spatial correlation was determined using the indicator semivariogram with a nested model fit approach. The mean N 2 O flux ranged from 25.3 to −0.2 ng N 2 O–N m −2 s −1 Probability distributions ranged in shape from reverse J‐shape through log normal to symmetrical. The majority of distributions were statistically different from each other, showing a lack of temporal stability. Mean N 2 O flux and distribution shape followed an event‐based/background emission pattern. High flux events had statistically similar, reverse J‐shaped distributions. As mean N 2 O flux decreased to a background level distribution, shape changed to log normal and symmetrical forms. A high nugget/sill ratio characterized the majority of sampling dates, although spatial dependency was generally moderate. Flux values in the fourth quartile tended to have a spatial dependency of 15 m, probably reflecting a topographic control at a landform element scale.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| 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 it