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Record W2167915891 · doi:10.1109/infovis.2005.5

An Interactive 3D Integration of Parallel Coordinates and Star Glyphs

2006· article· en· W2167915891 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 Calgary
Fundersnot available
KeywordsComputer scienceOffset (computer science)Focus (optics)Set (abstract data type)Computer graphics (images)Star (game theory)ImpressionContext (archaeology)Artificial intelligenceMathematics

Abstract

fetched live from OpenAlex

Parallel Coordinates are a powerful method for visualizing multidimensional data but, when applied to large data sets, they become cluttered and difficult to read. Star Glyphs, on the other hand, can be used to display either the attributes of a data item or the values across all items for a single attribute. Star Glyphs may readily provide a quick impression; however, since the full data set will require multiple glyphs, overall readings are more difficult. We present Parallel Glyphs, an interactive integration of the visual representations of Parallel Coordinates and Star Glyphs that utilizes the advantages of both representations to offset the disadvantages they have separately. We discuss the role of uniform and stepped colour scales in the visual comparison of non-adjacent items and Star Glyphs. Parallel Glyphs provide capabilities for focus-in-context exploration using two types of lenses and interactions specific to the 3D space.

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: Methods · Consensus signal: none
Teacher disagreement score0.978
Threshold uncertainty score0.151

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 communication0.0000.001
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 head0.013
GPT teacher head0.294
Teacher spread0.281 · 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

Citations60
Published2006
Admission routes1
Has abstractyes

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