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CONTROLLING VIRTUAL CLOUDS AND MAKING IT RAIN PARTICLE SYSTEMS IN REAL SPACES USING SITUATED AUGMENTED SIMULATION AND PORTABLE VIRTUAL ENVIRONMENTS

2012· article· en· W2029305388 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

Venue˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · 2012
Typearticle
Languageen
FieldComputer Science
TopicAugmented Reality Applications
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGeospatial analysisAugmented realitySituatedHuman–computer interactionComputer scienceSet (abstract data type)Virtual realityMultimediaArtificial intelligenceGeographyRemote sensing

Abstract

fetched live from OpenAlex

Abstract. The research described in this paper reports on the design, rationale, development and implementation of a set of new geospatial interfaces that combine multi-touch interaction, portable virtual environments, 'geosimulation gaming', and mobile augmented reality. The result is a set of new ways for us to combine the capabilities of geospatial virtual environments, augmented realitiy and geosimulation. These new hybrid interfaces deliver new geospatial information experiences – new ways of connecting spatial data, simulations, and abstract concepts to real spaces. Their potential to enhance environmental perception and learning must be explored.

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)0.002
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: none
Teacher disagreement score0.915
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.030
GPT teacher head0.286
Teacher spread0.256 · 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