Long-Term Cropping Effects on Agricultural Sustainability in Alar Oasis of Xinjiang, China
Bibliographic record
Abstract
Agricultural sustainability has become a major concern in arid regions of China. In order to better understand the influence of continuous cropping on soil quality, six experimental fields were established in the Alar Oasis of Xinjiang, including uncultivated land (as a zero year treatment duration) and five different continuous cropping years on cotton fields, with different cropping durations (5, 10, 15, 20 and 25 years, respectively). Thirteen soil indicators were selected including soil physicochemical properties, nutrient properties and enzymatic activities. The results show that duration of continuous cropping of cotton fields significantly influences a number of soil properties. Cultivation durations ranked according to soil quality indexes (SQI) are as follows: 15 years (0.828) > 20 years (0.816) > 10 years (0.668)> 5 years (0.548) > 25 years (0.377) > 0 years (0.205), and sustainable yield index (SYI) are as follows: 10 years (0.830) > 15 years (0.777) > 20 years (0.667) > 5 years (0.586) > 25 years (0.159).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".