MétaCan
Menu
Back to cohort
Record W2038219465 · doi:10.1145/642611.642702

GAZE-2

2003· article· en· W2038219465 on OpenAlexaff
Roel Vertegaal, Ivo Weevers, Changuk Sohn, Chris Cheung

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicGaze Tracking and Assistive Technology
Canadian institutionsQueen's University
Fundersnot available
KeywordsComputer visionGazeParallaxEye contactComputer scienceArtificial intelligenceEye trackingPerceptionComputer graphics (images)CommunicationPsychology

Abstract

fetched live from OpenAlex

GAZE-2 is a novel group video conferencing system that uses eye-controlled camera direction to ensure parallax-free transmission of eye contact. To convey eye contact, GAZE-2 employs a video tunnel that allows placement of cameras behind participant images on the screen. To avoid parallax, GAZE-2 automatically directs the cameras in this video tunnel using an eye tracker, selecting a single camera closest to where the user is looking for broadcast. Images of users are displayed in a virtual meeting room, and rotated towards the participant each user looks at. This way, eye contact can be conveyed to any number of users with only a single video stream per user. We empirically evaluated whether eye contact perception is affected by automated camera direction, which causes angular shifts in the transmitted images. Findings suggest camera shifts do not affect eye contact perception, and are not considered highly distractive.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.966
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0340.007

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 head0.012
GPT teacher head0.220
Teacher spread0.208 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations214
Published2003
Admission routes1
Has abstractyes

Explore more

Same topicGaze Tracking and Assistive TechnologyFrench-language works237,207