MétaCan
Menu
Back to cohort
Record W170366436

Real Time Distributed Collaboration

2002· article· en· W170366436 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicUsability and User Interface Design
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCollaborative softwareComputer scienceWork (physics)Computer-supported cooperative workHuman–computer interactionKnowledge managementEngineering
DOInot available

Abstract

fetched live from OpenAlex

Groupware for real time distributed collaboration allows people to work together at the same time, even when some or all participants and their work products are in different physical locations. To do this effectively, groupware and its components must support telepresence---a way of giving participants enough cues about each other to help them orchestrate their interactions---and teledata, a way of having participants bring into the meeting the materials and on-going work they wish to share with one another. Consequently, the design and implementation of a distributed system supporting real time collaboration must handle the human factors of how people collaborate as well as the expected technical issues. This article will describe some of these human factors, and how they are addressed by several groupware applications. Telepresence In face to face conversation and collaboration, people use and rely on many subtle cues to mediate their activities. These include voice inflection an...

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 score0.958
Threshold uncertainty score0.999

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)0.0010.002

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 head0.022
GPT teacher head0.238
Teacher spread0.215 · 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

Citations7
Published2002
Admission routes1
Has abstractyes

Explore more

Same topicUsability and User Interface DesignFrench-language works237,207