Spatial Scaling Analyses of Soil Physical Properties: A Review of Spectral and Wavelet Methods
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
Understanding the scaling properties of soil spatial variability is important for managing natural resources and protecting our environment. Our objective was to present methodology that has been used or has the potential to be used in spatial scaling of soil properties. The spectral and wavelet analyses were presented and illustrated using the soil hydraulic conductivity and other basic soil physical properties collected along a transect in Saskatchewan, Canada. We introduced periodogram, spectral analysis, simple squared coherency, and multiple coherency analyses as the frequency domain tools. For the wavelet analysis, the wavelet transform, cross wavelet spectrum, and simple wavelet coherency analysis were introduced. Detailed procedures and precautions for these analyses were also presented. The significance tests for different analyses were discussed and multiple testing for the wavelet analysis was introduced.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it