Analyses of the environmental impacts of an eco-industrial park using fuzzy cognitive maps
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents the application of fuzzy cognitive mapping analysis to study the impacts of developing an eco-industrial park (EIP). Within an EIP, one facility's waste is used as another's input, thereby reducing raw materials required and waste generated. While this is beneficial from a waste reduction approach, there are other factors such as colocation of secondary and tertiary services, increased population and vehicular traffic that follows as more industries colocate within a geographical area, which need to be considered. The combined impact on all these indirect effects has been studied here using a fuzzy cognitive map. The impact assessment found that utilizing byproducts/wastes provided by existing facilities significantly decreases waste disposal, but may lead to increased pollution due to increased activity level as additional businesses are established.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it