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Record W2101654639 · doi:10.1109/infvis.1996.559220

Minimally-immersive interactive volumetric information visualization

2002· article· en· W2101654639 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicData Visualization and Analytics
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsVisualizationComputer scienceInformation visualizationHuman–computer interactionCLARITYStereoscopyInteractive visualizationGlyph (data visualization)Rendering (computer graphics)Visual analyticsData visualizationComputer graphics (images)Artificial intelligenceComputer vision

Abstract

fetched live from OpenAlex

This paper describes a minimally immersive volumetric interactive system for information visualization. The system, SFA, uses glyph-based volume rendering, enabling more information attributes to be visualized than traditional 2D and surface-based information visualization systems. Two-handed interaction and stereoscopic viewing combine to produce a minimally immersive interactive system that enhances the user's three-dimensional perception of the information space, capitalizing on the human visual system's pre-attentive learning capabilities to quickly analyze the displayed information. The paper describes the usefulness of this system for the visualization of document similarity within a corpus of textual documents. SFA allows the three-dimensional volumetric visualization, manipulation, navigation, and analysis of multivariate, time-varying information spaces, increasing the quantity and clarity of information conveyed from the visualization as compared to traditional 2D information systems.

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 categoriesInsufficient payload (model declined to judge)
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 score0.978
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.004
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.019
GPT teacher head0.275
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

Quick stats

Citations13
Published2002
Admission routes1
Has abstractyes

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