Bibliographic record
Abstract
Abstract. Modeling water stable isotope transport in soil is crucial to sharpen our understanding of water cycles in terrestrial ecosystems. However, isotope and soil water transport are not fully coupled in current models. In this study, we developed MOIST: a MATLAB-based one-dimensional isotope and soil water transport model, a program that solves one-dimensional water, heat, and isotope transport equations simultaneously. Results showed that the MOIST model has good agreements to the theoretical tests and semi-analytical solutions of isotope transport under fixed boundary conditions. Furthermore, we validated the program with short- and long-term measurements from lysimeters studies. The overall Nash-Sutcliff efficiency coefficient (NSE) of soil water and deuterium (2H) transport for the short-term measurements are 0.66 and 0.69, respectively, with respective determine coefficient (R2) of 0.82 and 0.70, mean absolute error (MAE) of 0.02 m3 m-3 and 11.84 ‰. For the long-term lysimeter study, the overall NSE, R2, and MAE of simulated δ18O are 0.47, 0.49, and 0.92 ‰, respectively. These indices indicated the excellent performance of the MOIST model in simulating water flow and isotope transport in simplified ecosystems, suggesting a great potential of our program in promoting understandings of ecohydrological processes in terrestrial ecosystems.
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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 | 0.003 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.029 | 0.025 |
| Insufficient payload (model declined to judge) | 0.168 | 0.144 |
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".