Analysis of rural peat environmental risk using PROMETHEE method in Riau province, Indonesia
Bibliographic record
Abstract
Future global economic stability is under significant threat from environmental risks. Rural peat areas are particularly susceptible due to their elevated levels of hazard, vulnerability, and limited capacity. Acknowledging these risks is pivotal for fostering a low-carbon development trajectory. This study analyzes the environmental risk in rural peat areas within Riau Province. The PROMETHEE method, incorporating Shannon Entropy weighting for data analysis, was employed. The findings reveal that four regencies are exhibiting favorable environmental risk conditions and five regencies facing adverse conditions. The criteria influencing the environmental risk of rural peat in Riau Province showcase various positive and negative contributions across each regency. The sensitivity analysis underscores the resilience of forest fires and the social forest program in three regencies. Recognizing environmental risk can serve as a foundation for decision-makers to formulate sustainable development policies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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 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".