Comparing predictions of long-term soil carbon dynamics under various cropping management systems using K-model and CENTURY
Bibliographic record
Abstract
There is a strong demand for accurate estimates of long-term changes in soil organic carbon (SOC) with different agricultural practices under different soil and climate conditions. A process and analytic model, K-model, including a non-compartmental algorithm of soil carbon decomposition, was developed to simulate the changes of SOC under different cropping and soil management practices. This study evaluates the performance of K-model by comparing its predictions on SOC with measurements and predictions of CENTURY model, which is widely used for the similar purposes. Both K-model and CENTURY can predict the dynamics of SOC when site-specific soil and climate data are used to initialize simulations. Very similar annual carbon decomposition rates were simulated by the single carbon pool K-model and the 3-carbon pool CENTURY model. However, compared with experimental measurements of SOC, K-model produces relative smaller errors than CENTURY (<0.1 kg C m-2 vs. 0.08-0.48 kg C m-2, and within
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".