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Record W2134962426 · doi:10.11575/prism/30493

BubbleType: Enabling Text Entry within a Walk-Up Tabletop Installation

2008· article· en· W2134962426 on OpenAlexfundno aff
Uta Hinrichs, Holly Schmidt, Tobias Isenberg, Mark Hancock, Sheelagh Carpendale

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAffordanceStylusComputer scienceHuman–computer interactionProcess (computing)SimplicityText entryPublic spaceSpace (punctuation)MultimediaEngineeringArchitectural engineeringComputer vision

Abstract

fetched live from OpenAlex

We address the issue of enabling text entry for walk-up-and-use interactive tabletop displays located in public spaces. Public tabletop installations are characterized by a diverse target user group, multiperson interaction, and the need for high approachability and intuitiveness. We first define the design constraints of text-entry methods for public tabletop installations such as clear affordances, audience expertise, support of direct-touch interaction, visual appearance, space requirements, multi-user support, and technical simplicity. We then describe an iterative design process that was informed by these constraints and led to the development of two stylus keyboard prototypes—BubbleQWERTY and BubbleCIRCLE—for use in interactive public tabletop installations.

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.

How this classification was reachedexpand

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.773
Threshold uncertainty score0.681

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)0.0000.001

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 head0.020
GPT teacher head0.241
Teacher spread0.220 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2008
Admission routes1
Has abstractyes

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