Development of Agriculture Under the Influence of ESG Principles: Opportunities for Sustainable Soil Management
Bibliographic record
Abstract
In agricultural production, land serves as the basis for operations and the object of labor owing to its productivity determined by a specific property -soil fertility.Because of this property, land undeniably constitutes the main means of production in agriculture.Soil fertility largely determines the effectiveness of crop production.The study aims to identify the global trends, national challenges, and prospects of sustainable soil resource management in Central Asian countries.The study examines the core theoretical concepts pertaining to soil degradation.Through comparative and correlation analysis of the scores of the top 10 and Central Asian countries on the indicators and sub-indicators of the Global Food Security Index, the study identifies the place of Central Asian countries in the global ranking, including the condition of soil resources and its influence on food security.Recommended measures for managing soil resource risks are identified using an expert survey.The study concludes that the proposed measures for managing soil resources risks associated with soil degradation, soil pollution, violation of the optimal land use ratio, and the unsatisfactory phytosanitary condition of crops can mitigate the negative consequences for crop production in Central Asian countries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".