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Record W2222892795 · doi:10.4018/ijagr.2016010105

Developing a Compendium of Ideas on Using the Retrospective Approach to Mine for GIS Nuggets

2016· article· en· W2222892795 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.

Bibliographic record

VenueInternational Journal of Applied Geospatial Research · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCompendiumGeospatial analysisLimitingGeomaticsGeographic information systemModular designComputer scienceProcess (computing)Data sciencePrincipal (computer security)EngineeringGeographyArchaeologyRemote sensing

Abstract

fetched live from OpenAlex

The compendium of ideas paper addresses two needs: 1) Involving more people in the GIS retrospective program; 2) Creating an initial compilation of ideas which promote mining the various literatures – public, learned, popular (media), professional, etc. – for nuggets such as new ways to add to GIS technology, new reasons to add to geospatial information, and, new uses of GIScience research methods. Four design principles (connecting “ideas” and “nuggets”, using a modular approach, limiting modules to those critical to launch the project; and making it easy to modify modules) provide clear directions throughout the compendium-building process. And, each of the four modules (ideas about doing; ideas about objects of attention; principal GIS components as ideas and spawners of ideas; and, ideas as questions and questions as ideas) can be oriented to pursue general or particular interests that are held by all users of GIS technology and GIScience methods, techniques, and operations.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.136
GPT teacher head0.439
Teacher spread0.303 · 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