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Record W2015101735 · doi:10.1068/b2567

Space, Time, and Dynamics Modeling in Historical GIS Databases: A Fuzzy Logic Approach

2001· article· en· W2015101735 on OpenAlex
Suzana Dragićević, Danielle J. Marceau, Claude Marois

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironment and Planning B Planning and Design · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsUniversité de MontréalMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFuzzy logicInterpolation (computer graphics)Computer scienceShoreVisualizationMetropolitan areaSpacetimeSpace (punctuation)Data miningGeographyDatabaseArtificial intelligenceMotion (physics)Geology

Abstract

fetched live from OpenAlex

In this paper, a spatiotemporal interpolation approach for GIS modeling of urban growth dynamics is proposed. It is based on fuzzy logic theory using three different scenarios for temporal simulation, and two techniques for spatial simulation of urban change patterns. The notion of stages in the urban growth is taken into consideration as well as variables describing the speed and the mechanism of change. The simulation results are presented for three study sites from the north shore of the Montreal metropolitan area in Quebec, Canada, covering the period from 1956 to 1986. By comparing the simulation results with aerial photographs of the study area taken in 1958, 1971, 1975, and 1982, the proposed modeling approach is validated. The potential of this approach as a visualization technique is also discussed.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.759

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.049
GPT teacher head0.223
Teacher spread0.174 · 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