Suitability of hazard rating systems for air contamination from municipal solid waste dumps and improvements to enhance performance
Bibliographic record
Abstract
Close vicinity of uncontrolled municipal waste sites (or ‘waste dumps’) to well-populated communities makes the air contamination a prominent hazard from the waste dumps. The hazard rating systems, considered useful in prioritizing these sites for remediation, are investigated for their suitability to assess air contamination of municipal solid waste (MSW) dumps. Out of the eight systems employed in the study, six rating systems respond well to changes in site conditions when applied to hazardous waste sites. However for MSW sites, all eight rating systems give scores in a narrow range and do not perform well. One system is selected for improvement by modifying the indicators for waste quantity and rainfall and, introducing the indicators for waste composition and fresh waste quantity using expert judgment. The modified system performs well for MSW dumps, produces air contamination hazard ratings in a wider range, and responds to higher number of scenarios in sensitivity analysis, thus making it an appropriate tool for site prioritization for remediation.
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".