Modeling Carbon and Nitrogen Dynamics for Soil Management
Bibliographic record
Abstract
OVERVIEWS Introduction to Simulation of Carbon and Nitrogen Dynamics in Soils, M.J. Shaffer, L. Ma, and S. Hansen Carbon and Nitrogen Dynamics in Upland Soils, M.J. Shaffer and L. Ma Carbon and Nitrogen Dynamics in Wetland Soils, W.F. DeBusk, J.R. White, and K.R. Reddy A Review of Carbon and Nitrogen Processes in nine U.S. Soil Nitrogen Dynamics Models, L. Ma and M.J. Shaffer A Review of Carbon and Nitrogen Processes in European Soil Nitrogen Dynamics Models, M.B. McGechan and L. Wu A Review of Canadian Ecosystem Model - Ecosys, R.F. Grant Application of RZWQM for Nitrogen Management, L. Ma, M. Shaffer, and L. Ahuja Simulated Interaction of Carbon Dynamics and Nitrogen Trace Gas Fluxes Using the DAYCENT Model, S.J. Del Grosso, W.J. Parton, A.R. Mosier, M.D. Hartman, J. Brenner, D.S. Ojima, and D.S. Schimel NLEAP Water Quality Applications in Bulgaria, Dimitar Stoichev, Milena Kercheva, and Dimitranka Stoicheva Use of Simulations for Evaluation of Best Management Practices on Irrigated Cropping Systems, Jorge Delgado NLEAP (NLEAP on STELLA) - A Nitrogen Cycling Model with a Graphical Interface: Implications for Model Developers and Users, S. Bittman, D.E. Hunt, M.J. Shaffer, and T.L. Nelson NLEAP Internet Tools for Estimating NO3-N Leaching and N2O Emissions, M. Shaffer, K. Lasnik, X. Ou, R. Flynn, and C. Xu Modelling the Effects of Manure and Fertilizer Management Options on Soil Carbon and Nitrogen Processes, M.B. McGechan, D.R. Lewis, L. Wu, and I.P. McTaggart Parametrisation of Soil Nitrogen Transport Models by Use of Laboratory and Field Data, E. Priesack, S. Achatz, and R. Stenger Application of the Daisy Model for Short- and Long-Term Simulation of Soil Carbon and Nitrogen Dynamics, L.S. Jensen, T. Mueller, S. Bruun, and S. Hansen Modelling Nitrate Leaching at Different Scales - Application of the Daisy Model, Soren Hansen, Christian Thirup, Jens Christian Refsgaard, and Lars Stoumann Jensen Performance of a Nitrogen Dynamics Model Applied to Evaluate Agricultural Management Practices, K.C. Kersebaum and A.J. Beblik Modeling N Behavior in the Soil and Vadoze Environment Supporting Fertilizer Management at the Farm Scale, Juan David Pineros Garcet, Amaury Tilmant, Mathieu Javauz, and Marnik Vanclooster Modeling Transformations of Soil Organic Carbon and Nitrogen at Differing Scales of Complexity, R.F. Grant
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".