Surface flow–interflow-coupled nitrogen loss in gray fluvo-aquic farmland soils in the Anhui Section of the Huaihe River Basin, China
Bibliographic record
Abstract
To reveal the characteristics of nitrogen loss and their coupling relations in the process of surface flow and interflow under various rainfall intensities in gray fluvo-aquic soil areas, the coupling loss characteristics of total nitrogen (TN), nitrate nitrogen (NO3−-N), and ammonium nitrogen (NH4+-N) in the surface flow and interflow under three rainfall intensities (60, 80, and 110 mm·h−1) at a slope of 5° were studied using an artificial rainfall simulation. The results showed that (1) runoff yield and TN concentration were proportional to the rainfall intensity, with higher runoff concentrations of TN in the initial stage, and (2) surface flow yield, which was the main output mode of farmland runoff, was higher than interflow yield under a range of rainfall intensities. The average concentration of NO3−-N in surface flow decreased with increasing rainfall intensity, whereas the opposite was true in interflow. The main loss path of NO3−-N was interflow, whereas the main loss path of NH4+-N was the surface flow; NO3−-N was the main form of TN loss. The surface flow was the main loss path of soil nitrogen loss in farmland, and the runoff yield was an important factor in controlling nitrogen loss.
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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 | 0.001 | 0.001 |
| 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".