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Record W2257894180

Generating adaptable user interfaces using rich internet application

2009· article· en· W2257894180 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

VenueAnnual Conference on Computers · 2009
Typearticle
Languageen
FieldComputer Science
TopicUsability and User Interface Design
Canadian institutionsScience North
Fundersnot available
KeywordsComputer scienceUser interfaceXMLPersonalizationGraphical user interfaceNatural user interfaceUser interface designMarkup languageHuman–computer interaction10-foot user interfaceThe InternetWorld Wide WebGraphical user interface testingKey (lock)Post-WIMPComponent (thermodynamics)User FriendlyXHTMLInterface (matter)Operating system
DOInot available

Abstract

fetched live from OpenAlex

Personalization of interfaces by each user using user-friendly forms is a key concept to ensure interface accessibility. In this direction, we are using Extensible Markup Language (XML) as data source to generate interfaces. All users can adapt interface by modifying each component style, properties and events and modifications are saved as XML content. This user interfaces can be run as desktop application or in browser. This result in the generation of personalized multimodal user interfaces can be useful for many kinds of applications. Key-Words: Graphical User Interface; Adaptable User Interfaces, Rich Internet Application

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 categoriesMeta-epidemiology (narrow)
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 score0.864
Threshold uncertainty score1.000

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 communication0.0010.001
Open science0.0010.000
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 head0.053
GPT teacher head0.288
Teacher spread0.235 · 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