Soil Properties, Yield, and Landscape Relationships in South-Central Saskatchewan Canada
Bibliographic record
Abstract
Soil water and nutrient availability are major limiting factors for crop production in the Canadian prairies. Most variations in soil properties observed across prairie farm fields are the result of the effect of landscape on water and soil redistribution. The relationships among soil chemical properties (pH, electrical conductivity, organic matter, and available nutrients), soil water, elevation, and canola seed yield were investigated in a transect across a hummocky, undulating farm field in the Brown soil zone of south-central Saskatchewan. Overall, seed yield was highest in foot slope positions in the landscape where soil organic matter, nutrients, and available water content were higher. Correlations between soil properties and seed yield were highest for pH (R = −0.46, P < 0.01), which was followed by organic C % (R = 0.27, P < 0.05), water content (R = 0.23), extractable potassium (K) (R = 0.18) and nitrogen (N) and phosphorus (P) supply rates to exchange resin membranes (R = 0.15). Extractable N and P were poorly correlated with seed yield (R < 0.1). The landscape region with soil parameters and yield closest to the average for the entire transect was the back slope region, suggesting that in similar landscapes, this region would be most appropriate for selection as a representative benchmark sampling site.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".