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Record W2132364492 · doi:10.1139/s07-033

GIS-based locational analysis of collection bins in municipal solid waste management systems

2008· article· en· W2132364492 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsnot available
Fundersnot available
KeywordsMunicipal solid wasteSite selectionSolid waste managementGeographic information systemBinComputer scienceOperations researchWaste collectionWaste managementEnvironmental scienceEnvironmental economicsEngineeringAlgorithmGeography

Abstract

fetched live from OpenAlex

Solid waste management systems currently receive wide attention, from both economic and environmental planners, because of their complexity during coordination of various management strategies. The efficiency and cost effectiveness of route optimization and disposal site selection depend largely upon the appropriate placement of storage bins and their corresponding command area for waste contribution. The present paper illustrates a geographic information system (GIS) based algorithm for optimal location and number of storage bins, considering p-median constrained model, based on Indian guidelines for Municipal Solid Waste Rules. The algorithm also computes the contributing command area of solid waste to a particular bin, based on the shortest distance, with descending slope for ease in solid waste collection.

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.

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: Empirical
Teacher disagreement score0.187
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.009
GPT teacher head0.206
Teacher spread0.197 · 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