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Record W2942309445 · doi:10.1145/3290605.3300332

Finding Information on Non-Rectangular Interfaces

2019· preprint· en· W2942309445 on OpenAlex
Florine Simon, Anne Roudaut, Pourang Irani, Marcos Serrano

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
Typepreprint
Languageen
FieldComputer Science
TopicGaze Tracking and Assistive Technology
Canadian institutionsUniversity of Manitoba
FundersEngineering and Physical Sciences Research CouncilAgence Nationale de la Recherche
KeywordsComputer scienceHuman–computer interactionInterface (matter)User interfaceVisual searchArtificial intelligenceProgramming language

Abstract

fetched live from OpenAlex

With upcoming breakthroughs in free-form display technologies, new user interface design challenges have emerged. Here, we investigate a question, which has been widely explored on traditional GUIs but unexplored on non-rectangular interfaces: what are the user strategies in terms of visual search when information is not presented in a traditional rectangular layout? To achieve this, we present two complementary studies investigating eye movements in different visual search tasks. Our results unveil which areas are seen first according to different visual structures. By doing so we address the question of where to place relevant content for the UI designers of non-rectangular displays.

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 categoriesInsufficient payload (model declined to judge)
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 score0.866
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 communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.018
GPT teacher head0.260
Teacher spread0.242 · 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

Citations13
Published2019
Admission routes1
Has abstractyes

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