Assessing Landfill Locations for Waste Management for the City of Abu Dhabi Using GIS
Bibliographic record
Abstract
Landfill sites receive 92 % of the total annual solid waste produced by municipalities in the Emirate of Abu Dhabi. Landfill siting is an extremely difficult task because site selection depends on different factors and regulations. To ensure that an appropriate site is chosen, a systematic process should be developed and followed. In this study candidate sites for an appropriate landfill location for the Abu Dhabi municipal area are determined by integrating geographic information systems (GIS) and multi-criteria evaluation (MCE) analysis. To identify appropriate landfill sites, 19 input map layers, including proximity to urban areas, proximity to wells and water table depth, geology and topography, proximity to touristic and archaeological sites, distance from the road network, distance from drainage networks, land slope, and so on, were used in constraint mapping. A final map was created identifying potential sites suitable for the location of a landfill. The results revealed that 30 % of the study area...
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".