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Record W4403471791 · doi:10.3390/engproc2024076010

A Sustainable Approach to Waste Management: Selecting the Optimal Landfill Site in Saskatchewan, Canada

2024· article· en· W4403471791 on OpenAlexaffabout
Md. Shahariar Ahmed, Sheikh Md Shahadat Kabir, Anica Tasnim, Arafat Sultan Khan, Kabita Bhowmik, Golam Kabir

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsEnvironmental scienceWaste managementSite selectionEnvironmental planningEngineering

Abstract

fetched live from OpenAlex

Solid waste management is a crucial task for municipalities in disposing of city waste. Overcoming socioeconomic obstacles in finding appropriate landfill sites involves a multifunctional team using a process that includes selecting criteria and alternatives. In this study, the FUZZY Analytical Hierarchy Process (AHP) and FUZZY TOPSIS were used to rank five landfill alternatives based on seven criteria. Additionally, Interpretive Structural Modeling (ISM) was employed to establish hierarchical relationships between criteria. MICMAC analysis identified dominant and dependent factors. The study found that Land Capacity carries the highest weight, and the Central Landfill site is the most suitable location. Land Capacity is the dominant factor, while land surface temperature has minimal impact. Roads and communication networks have the highest driving power. The project’s findings can guide the selection of landfill sites and contribute to the development of new sites based on the criteria discussed and their relationships.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.488
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.197
Teacher spread0.191 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2024
Admission routes2
Has abstractyes

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