Simulation of Nitrate‐N Leaching in No‐Till Fields with DRAINMOD‐N II in a Cold‐Humid Region
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Conservation agriculture, especially no‐tillage, has proven to become sustainable farming in many agricultural environments globally. In spite of advantages of no‐till systems, this practice may result in excess infiltration into the soil and can enhance the movement of mobile nutrients and some pesticides to subsurface drains and groundwater along preferential pathways. The goal of this study was to evaluate the capacity of DRAINMOD‐N II to simulate subsurface nitrate‐N leaching in no‐till fields in Truro, Nova Scotia, Canada, from 2003 to 2006. The model performance was first evaluated by comparing observed and simulated drain outflow data that is an essential prerequisite for the model to obtain a proper prediction of NO 3 ‐N movement, and then by comparing observed and simulated NO 3 ‐N concentration in no‐till fields using three statistical indices, relative root mean square error (RRMSE), average absolute deviation (AAD) and the correlation coefficient ( R 2 ). The RRMSE, AAD and R 2 for the validation period were determined to be 1.09, 1.85 and 0.83 mm for drain outflow, and 1.43, 0.51 and 0.79 mg l −1 for NO 3 ‐N concentration respectively. The results showed that DRAINMOD‐N II predicted NO 3 ‐N leaching reasonably well in drainage outflow of no‐till fields over the whole period. Copyright © 2018 John Wiley & Sons, Ltd.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it