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Record W1971812842 · doi:10.1145/2677199.2680572

PaperFold

2015· article· en· W1971812842 on OpenAlex
Antônio Tadeu A. Gomes, Roel Vertegaal

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
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsQueen's University
Fundersnot available
KeywordsViewportComputer scienceHuman–computer interactionMobile deviceFolding (DSP implementation)Computer graphics (images)World Wide WebEngineering

Abstract

fetched live from OpenAlex

In this paper, we investigate the use of shape changes in a multi-segmented mobile device for triggering viewport transformations in its graphical interface. We study PaperFold, a foldable device with reconfigurable thin-film electrophoretic display tiles. PaperFold enables users to attach, reorient and fold displays in a mobile form factor that is thin and lightweight even when fully collapsed. We discuss how our design was informed by a participatory study that resulted in 14 preferred shape changes. In a subsequent study, we asked users to rank the utility of shape changes for triggering common view operations in map and text editing applications. Results suggest participants were able to attribute specific view operations as automated responses to folding, attaching, reorienting or detaching displays. Collated or full screen views were preferred when users collocated two displays. When adding a third display, alternative views such as toolbars or a list of apps were suggested. Showing 3D views was strongly associated with folding PaperFold segments into a three dimensional structure.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
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 science0.0000.000
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 head0.037
GPT teacher head0.261
Teacher spread0.223 · 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

Citations38
Published2015
Admission routes1
Has abstractyes

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