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Record W2664273831

Design Considerations for Enhancing Word-Scale Visualizations with Interaction

2015· preprint· en· W2664273831 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

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2015
Typepreprint
Languageen
FieldComputer Science
TopicData Visualization and Analytics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceFocus (optics)Word (group theory)VisualizationScale (ratio)Human–computer interactionReading (process)Space (punctuation)Data visualizationInteraction designInformation visualizationNatural language processingArtificial intelligenceLinguistics
DOInot available

Abstract

fetched live from OpenAlex

This paper presents a design space for interaction with word-scale visualizations. Most sparklines and word-scale visualizations are static and do not support any interaction. However, when word- scale visualizations are used in digital environments, interaction can enhance their use by allowing various data manipulation and man- agement operations. Our design space covers where, when, and how interaction can be triggered for word-scale visualizations em- bedded in a text document. It also includes how and when to transi- tion from a view where the text with word-scale visualizations is the focus (document-centric view) to a view in which the visualizations becomes the reading focus (visualization-centric view).

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.901
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.049
GPT teacher head0.302
Teacher spread0.254 · 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