Selection of Wastewater Treatment for Small Canadian Communities
Bibliographic record
Abstract
An integrated fuzzy analytic hierarchy process (F-AHP) and grey relational analysis (GRA) were used to facilitate the selection of appropriate wastewater treatment (WWT) alternatives for small communities. Seven commonly used WWT technology alternatives were assessed for a hypothetical small community in Canada. The assessment was based on the holistic evaluation of technical, economic, social, and environmental criteria, with each criterion composed of several subindices. The weights of criteria and subindices were determined using F-AHP to address nonprobabilistic uncertainties, such as vagueness and ambiguities in human thoughts resulting from the subjective weighting process. The weighted criteria were then aggregated and, based on the aggregation results, alternatives were ranked using GRA. The results from the integrated approach show that constructed wetland, stabilized pond, and extended aeration lagoon (EAL) are the top three appropriate WWT technologies for small Canadian communities. It was also found that the fuzzy-based approach and the nonfuzzy-based approach generated different rankings for the alternatives, indicating that fuzzy uncertainties could affect the decision-making process.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".