Estimating carbon retention in soils amended with composted beef cattle manure
Bibliographic record
Abstract
Composted cattle manure is often used as a soil amendment to replenish nutrient pools and to supply a source of stable C. Compost composition affects the availability of nutrients and the stability of C following the addition of compost to soil. We investigated C mineralization in a loamy sand and a loam soil amended with nine composts, two fresh manures and alfalfa (Medicago sativa L.) hay at a target rate of 10 mg total C g-1 soil. Soils were incubated at 25°C for 168 d. There was a significant interaction between amendment and soil type on C mineralization but generally, the effect of soil texture on amendment decomposition was small. The composts were very dissimilar in composition and resulted in substantial differences in the amount of C retained in the soils (2-39% C added evolved as CO2). Total C evolved during the incubation period could be predicted from the NH4-N content and the NH4-N/NO3-N ratio of the composted manures (R2 = 0.91–0.93). Estimation of the C retained in soils amended with compost as a function of simple chemical properties of the compost provides an important tool for evaluating the effectiveness of compost as a soil amendment, helping to calculate net retention of C. Key words: Compost, mineralization, soil carbon, amendment
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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 | 0.001 |
| 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) | 0.000 | 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".