Influence of Long-term Application of Feedlot Amendments to Cropland on Ground Elevation, Ah Horizon Depth, and Soil Color
Bibliographic record
Abstract
Few studies have examined the effect of long-term application of feedlot manure on ground elevation, Ah horizon depth, and color of surface soil. The objective of this study was to examine the effect of manure type (stockpiled vs. composted feedlot manure), bedding (straw vs. wood chips), and application rate (13, 39, and 77 Mg ha−1 dry wt.) on these soil properties after 17 annual applications. There was also one inorganic (IN) fertilizer treatment and an unamended control. Elevations were measured using a total station, and the Munsell value and chroma measured on field soil and on fine-ground (<150 μm) soil using color charts. Manure type and bedding had no significant (P > 0.05) effect on relative elevation and Ah depth, but relative elevation and Ah depth increased with greater application rates (10.7 cm increase in relative elevation at 77 Mg ha−1). The Munsell color value was significantly lower or darker for amended than unamended soils and shifted the Chernozemic soil Great Group classification for some treatments from Dark Brown to Black. Overall, greater rates of feedlot manure increased the relative elevation and Ah depth of amended soils and made the surface soil darker, but manure type and bedding had no effect.
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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".