Livestock manure improves acid soil productivity under a cold northern Alberta climate
Bibliographic record
Abstract
The acid-ameliorating properties of feedlot cattle manure on barley and canola productivity in acid soils were evaluated from 2003 to 2007 at Fort Vermilion and Beaverlodge research stations in northern Alberta, Canada. Treatments included Control, NP fertilizer, Lime + NP fertilizer and manure at 80 (M80) and 160 (M160) Mg ha-1. Manure and lime were applied once in 2003 and NP fertilizer was applied annually. Manure significantly increased soil pH from around 4 to >5 and this increase persisted over the 4-yr period. At Fort Vermilion, M160 reduced soil 0.01 M CaCl2 extractable Al and Mn contents from 2.9 and 11.7 mg kg-1 (Control) to 1.1 and 8.9 mg kg-1 and barley straw Mn content from 313 (Control) to 220 mg kg-1. Soil P (Mehlich 3) and K (0.01 M CaCl2 extractable) contents in M160 were more than two times those in the Control, while values from fertilizer treatments were not different from the Control. Crop grain N, P and K uptakes and yields in M160 were twice those of the Control. In northern Alberta, manure application to acid soils at a rate of 160 Mg ha-1 once every 4 yr had the same effectiveness as Lime + NP fertilizer in increasing soil pH and improving soil fertility and crop productivity at the field scale.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 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".