Can soil clay content predict ammonia volatilization losses from subsurface-banded urea in eastern Canadian soils?
Bibliographic record
Abstract
To determine how soil physical and chemical characteristics affect NH3 volatilization, we measured NH3 losses from eight different eastern Canadian soils with various soil clay contents and cation exchange capacities (CEC). Losses were measured from soil mesocosms banded (0.05 m depth) with urea (equivalent of 140 kg N ha−1) in a dynamic chamber system fitted with an acid trap; with soil properties measured in parallel mesocosms. Regression analysis indicated a negative relationship between 28 d of NH3 volatilization losses and soil clay content (P < 0.001; R2 = 0.978), CEC (P < 0.001; R2 = 0.941), and buffer capacity (P = 0.006; R2 = 0.772), and positive relations with maximum change in soil pH (P = 0.015; R2 = 0.670) and maximum water-extractable NH4+ (P = 0.010; R2 = 0.721). A 90% reduction in NH3 losses occurred when clay content increased from 10% to 20%. Also, the correlation between water-extractable NH4+ and NH3 loss and a lack of correlation between salt-extractable (1 mol L−1 KCl) NH4+ and NH3 loss indicate that NH4+ bound to cation exchange sites does not contribute to the rapid NH3 volatilization. However, more research on soils of different mineralogy is required to ascertain whether this holds in other regions as well.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".