Simplified measurement-based simulation model of soil-plant phosphorus cycles in long-term agro-systems
Bibliographic record
Abstract
Actual phosphorus models are created in conventional tillage system. In addition, most simulation models are process-based, which need mathematical descriptions of fundamental physio-chemical mechanisms. The small time-step e.g. daily might not fit long-term simulation. In this study, a P model based on measured data was created to simulate the evolution of soil P status along soil profile in long-term. In P model, a soil zone was divided into 30 grids according to vertical (0-5, 5-10, 10-20, 20-30 and 30-40 cm) and lateral (0-10, 10-20 and 20-30 cm for two sides into inter-row) coordinates. For each grid, P stock was defined as total amount of phosphate ions in solid and liquid phases. The P inputs and P outputs of each grid such as fertilizer, uptake, runoff and leaching were estimated with measured data in every time-step (yearly). The P status (phosphate ion concentration in soil solution) was calculated from P stock and P budget in each time step. The simulation was conducted with two tillage systems [moldboard plough (MP) and no-till (NT)].The P model managed to simulate the evolution of P status along soil profile in MP and NT during 25 years; while it was a homogenous distribution of soil P within 0-20 cm in MP. The simulated results indicated that higher accumulation of soil P in upper layers might lead to a lower use of soil P stocked in sub-soil by crop uptake. However, the model still needs validation and adjustment of parameters to form more accurate results.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".