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Record W4214543327 · doi:10.1145/572015.572016

The "mighty mouse" multi-screen collaboration tool

2002· article· en· W4214543327 on OpenAlexaff
Kellogg S. Booth, Brian Fisher, Chi Jui Raymond Lin, Ritchie Argue

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicPersonal Information Management and User Behavior
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer sciencePersonalizationHuman–computer interactionCollaborative softwareVariety (cybernetics)Domain (mathematical analysis)Protocol (science)MultimediaWorld Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

Many computer operating systems provide seamless support for multiple display screens, but there are few cross-platform tools for collaborative use of multiple computers in a shared display environment. Mighty Mouse is a novel groupware tool built on the public domain VNC protocol. It is tailored specifically for face-to-face collaboration where multiple heterogeneous computers (usually laptops) are viewed simultaneously (usually via projectors) by people working together on a variety of applications under various operating systems. Mighty Mouse uses only the remote input capability of VNC, but enhances this with various features to support flexible movement between the various platforms, "floor control" to facilitate smooth collaboration, and customization features to accommodate different user, platform, and application preferences in a relatively seamless manner. The design rationale arises from specific observations about how people collaborate in meetings, which allows certain simplifying assumptions to be made in the implementation.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.005

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 head0.351
GPT teacher head0.432
Teacher spread0.082 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations1
Published2002
Admission routes1
Has abstractyes

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