MétaCan
Menu
Back to cohort
Record W2105315098 · doi:10.1109/have.2009.5356120

A mobile 3D user interface for interaction with ambient audio visual environments

2009· article· en· W2105315098 on OpenAlexaff
Ali Asghar Nazari Shirehjini, Shervin Shirmohammadi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAugmented Reality Applications
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceHuman–computer interactionUser interfaceMobile deviceVisualizationMobile interactionInterface (matter)User interface designOrientation (vector space)Ambient intelligenceUser experience designArtificial intelligenceWorld Wide Web

Abstract

fetched live from OpenAlex

This paper describes concepts, design, implementation, and performance evaluation of a 3D-based user interface for accessing Ambient Intelligence Environments (AmIE). The generic interaction model of the described work addresses some major challenges of Human-Environment-Interaction such as cognitive overload and manual device selection, loss of user control, missing system image or over-automation. 3D visualization and 3D UI, acting as the central feature of the system, create a logical link between physical devices and their virtual representation on the user's PDA or other mobile devices. By doing so, the user can easily identify a device within the environment based on its position, orientation, and form, and access the identified devices through the 3D interface for direct manipulation within the scene.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.003

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 head0.011
GPT teacher head0.291
Teacher spread0.280 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations7
Published2009
Admission routes1
Has abstractyes

Explore more

Same topicAugmented Reality ApplicationsFrench-language works237,207