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Record W1515135756 · doi:10.11575/prism/30743

RAPIDLY PROTOTYPING SINGLE DISPLAY GROUPWARE THROUGH THE SDGTOOLKIT

2003· article· en· W1515135756 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

VenuePRISM (University of Calgary) · 2003
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceCursor (databases)Human–computer interactionProgrammerCollaborative softwareWindow (computing)Computer graphics (images)Input deviceMulti-touchMultimediaWorld Wide WebProgramming languageComputer hardwareArtificial intelligence

Abstract

fetched live from OpenAlex

Researchers in Single Display Goupware (SDG) explore how multiple users share a single display such as a computer monitor, a large wall display, or an electronic tabletop display. Yet todays personal computers are designed with the assumption that one person interacts with the display at a time. Thus researchers and programmers face considerable hurdles if they wish to develop SDG. Our solution is the SDGToolkit, a toolkit for rapidly prototyping SDG. SDGToolkit automatically captures and manages multiple mice and keyboards, and presents them to the programmer as uniquely identified input events relative to either the whole screen or a particular window. It transparently provides multiple cursors, one for each mouse. To handle orientation issues for tabletop displays (i.e., people seated across from one another), programmers can specify a participants seating angle, which automatically rotates the cursor and translates input coordinates so the mouse behaves correctly. Finally, SDGToolkit provides an SDG-aware widget class layer that significantly eases how programmers create novel graphical components that recognize and respond to multiple inputs.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score0.461

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 science0.0010.000
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 head0.014
GPT teacher head0.210
Teacher spread0.195 · 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