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Record W4205311455 · doi:10.1068/b3003rvw

Reviews: Time-Integrative Geographic Information Systems: Management and Analysis of Spatio-Temporal Data, Time-Integrative Geographic Information Systems: Management and Analysis of Spatio-Temporal Data, Environmental Modelling with GIS and Remote Sensing, Local Strategic Partnerships: Lessons from New Commitment to Regeneration, Inclusive Design: Designing and Developing Accessible Environments, the European Dimension of British Planning, Cities for the New Millennium, Valuing Environmental and Natural Resources: The Econometrics of Non-Market Valuation, Uncertainty and the Environment: Implications for Decision Making and Environmental Policy, Spatial Data Quality, Innovations in GIS 8. Spatial Information and the Environment, Planning for Crime Prevention: A Transatlantic Perspective, Java Programming for Spatial Sciences, Geographical Data: Characteristics and Sources, a New Kind of Science

2003· article· en· W4205311455 on OpenAlexaff
Suzana Dragićević, M. Smith, Michael F. Goodchild, Claudio De Magalhães, Huw Thomas, William Walton, Peter Hall, Ian Moffatt, Daniel Z. Sui, Peter Halls, Victor Mesev, David Ashby, Sanjay Rana, Paul Williamson, Britton Harris

Bibliographic record

VenueEnvironment and Planning B Planning and Design · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsVictoria ParkSimon Fraser University
Fundersnot available
KeywordsGeographic information systemLocal information systemsInformation systemGIS and public healthComputer scienceData scienceTemporal databaseData managementData miningGeographyRemote sensingEngineering

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.789
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0020.003
Scholarly communication0.0000.001
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 head0.097
GPT teacher head0.329
Teacher spread0.232 · 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.

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

Citations0
Published2003
Admission routes1
Has abstractno

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