Recovery of Agricultural Areas Affected by Traditional Gold Mining: Sustainable Food Supply Stability
Bibliographic record
Abstract
This study aims to analyze the recovery of the agricultural area’s function affected by the Poboya traditional gold mining in supporting the stability of sustainable food supply. We began the research by examining the existing mining land conditions through spatial analysis (land cover and land use changes from 2010 to 2019). Apart from that, it also analyzed the land’s health was through the soil’s physical and chemical properties, especially mercury. The observation proved that changes in the land’s cover and uses lead to decreased land quality and degradation. The existing condition showed heavy metals, particularly mercury, mostly polluted agricultural land in the mining area. The model design produced by this study may 1) emphasize land arrangement; 2) revegetation design with forestry, plantation, and food crops; 3) domesticated plant; and 4) environmental monitoring, concerning monitoring of soil quality, monitoring of erosion and sedimentation, water quality, acid mine drainage, successful revegetation, and others. These four aspects expect to help suppress the rate of land degradation in agriculture located in ex-mining areas and reduce forest destruction in the Grand Forest Park area.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".