Aggregate size distribution and associated carbon and nitrogen in mulched winter wheat and spring corn
Bibliographic record
Abstract
The influence of surface mulching on soil aggregation and associated carbon (C) and nitrogen (N) varies by mulching materials and crop types. The 6 yr effect of straw mulching (SM), plastic film mulching (PM), and no mulching (CK) on soil aggregation and associated C and N concentrations at 0–20 and 20–40 cm soil layers were studied under dryland winter wheat (Triticum aestivum L.) and spring corn (Zea mays L.) in the Loess Plateau of China. Regardless of crop types, aggregate proportion was greater in macroaggregates (2.00–10.00 mm), but lower in microaggregates (<0.50 mm) with mulching than without in both soil layers. The mean weight diameter of aggregates was greater with SM and PM than CK. Compared with CK and PM, SM increased soil organic C (SOC) and total N (STN) concentrations in both macroaggregates and bulk soil at 0–20 cm. Aggregate proportion and soil C and N concentrations at both depths were more pronounced in winter wheat than spring corn. The recovery rates of bulk soil SOC and STN in aggregates varied from 94% to 107%. Straw and plastic film mulching enhanced soil aggregation compared with no mulching. Straw mulching was more effective in increasing SOC and STN concentrations at the surface layer in dryland winter wheat and spring corn.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".