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Record W2089274405 · doi:10.4236/jgis.2011.31004

A GIS-Based Multicriteria Decision Analysis Approach for Mapping Accessibility Patterns of Housing Development Sites: A Case Study in Canmore, Alberta

2011· article· en· W2089274405 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Geographic Information System · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsWestern UniversityYork University
Fundersnot available
KeywordsRaster graphicsGeographic information systemAnalytic hierarchy processComputer scienceProcess (computing)HierarchyDecision support systemGeographyData miningOperations researchCartographyEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

This paper presents a Geographic Information System (GIS) based multicriteria decision analysis approach for mapping accessibility patterns of housing development sites in Canmore, Alberta. The approach involves integrating two multicriteria decision methods (Analytical Hierarchy Process and Ordered Weighted Aver-aging) in a raster GIS environment, and incorporating the linguistic quantifier concept as a method for ob-taining the order weights. The approach facilitates a wide range of location (decision) strategies to be gener-ated and examined. The aim of the study is to help the housing development authorities in addressing the uncertainty involved in the decision making process, achieving a better understanding of the alternative ac-cessibility patterns. It also assists the authorities in evaluating and prioritizing the potential housing devel-opment sites in terms of accessibility levels.

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)0.008
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.345
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.003
Science and technology studies0.0010.000
Scholarly communication0.0000.002
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 head0.071
GPT teacher head0.316
Teacher spread0.245 · 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