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Record W2008951641 · doi:10.1145/2046396.2046438

Embedding interface sketches in code

2011· article· en· W2008951641 on OpenAlexaff
James Simpson, Michael Terry

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicUsability and User Interface Design
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceASCIIEmbeddingRendering (computer graphics)User interfaceInterface (matter)Programming languageCode (set theory)Cursor (databases)Human–computer interactionComputer graphics (images)Operating systemSet (abstract data type)DatabaseArtificial intelligence

Abstract

fetched live from OpenAlex

This paper presents a user interface (UI) design tool, GUIIO, which uses ASCII text as its medium for rendering interface components. Like other UI design tools, GUIIO allows individuals to create and manipulate UI components as first-class objects. However, GUIIO has the advantage that its UI designs can be embedded directly within the program code itself. We implemented GUIIO as an extension to an existing development environment. As a result, developers can fluidly transition from editing code to editing the UI mock-up, with the text editor automatically switching its mode from code editing to UI editing as a function of the location of the cursor. By rendering UIs as ASCII art, GUIIO fills an important gap in the design, implementation, and revision of UIs by providing a highly portable and immediately accessible visual representation of the UI that embeds with the code itself.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0040.005
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0190.003

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 head0.087
GPT teacher head0.297
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations2
Published2011
Admission routes1
Has abstractyes

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