Influence of long-term feedlot manure amendments on soil hydraulic conductivity, water-stable aggregates, and soil thermal properties during the growing season
Bibliographic record
Abstract
Long-term application of feedlot manure to cropland may change the physical properties of soils. We measured selected soil (surface) physical properties of a Dark Brown Chernozemic clay loam where different amendments were annually applied for 15 (2013), 16 (2014), and 17 (2015) yr. The treatments were stockpiled (SM) or composted (CM) manure with either straw (ST) or wood-chip (WD) bedding applied at three rates (13, 39, and 77 Mg ha−1) and an unamended control. The effect of selected or all treatments on selected properties was determined in 2013–2015. These properties included field-saturated (Kfs) and near-saturated hydraulic conductivity or K(ψ), bulk density (BD), volumetric water content, soil temperature, soil thermal properties, and wet aggregate stability. The hypotheses that selected soil physical properties would improve more for treatments with greater total carbon in the amendments (SM > CM, WD > ST) was rejected. The exceptions were significantly (P ≤ 0.05) lower soil BD for SM than CM and WD than ST for certain dates, and lower soil thermal conductivity for WD than ST. Most soil physical properties generally had no response to 15–17 yr of annual applications of these feedlot amendments, but a few showed a positive response.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".