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Record W4300531409 · doi:10.1145/2534903.2534914

An empirical study on the user's context in mobile videoconferencing devices

2013· article· en· W4300531409 on OpenAlexaff
Ignacio Calvo, Tomás Dorta, Jean‐Marc Robert

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicContext-Aware Activity Recognition Systems
Canadian institutionsPolytechnique MontréalBombardier (Canada)Université de Montréal
Fundersnot available
KeywordsVideoconferencingContext (archaeology)Computer scienceMobile deviceEmpirical researchMultimediaHuman–computer interactionWorld Wide WebGeographyMathematicsStatistics

Abstract

fetched live from OpenAlex

This paper presents an exploratory empirical study on the user's context in mobile videoconferencing in order to improve the user interface of mobile video devices. Through the rich exchange of information, mobile video communication can provide a better sense of presence than other means of communication. Yet the current mobile interfaces lack the flexibility required to be creative and more meaningful in a videoconference exchange. We conducted observations with 16 participants in three activities where their conversations, reactions and behaviours were observed. Two focus groups were used to identify habits formed from regular use. Results suggest an important difference between the use of the front-facing or back-facing camera and the importance of offering tools that provide more control over the video exchange. From theses results, the study proposes several design recommendations for mobile video communication interfaces in order to support the construction of the user's mobile context.

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)0.003
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.067
GPT teacher head0.328
Teacher spread0.261 · 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 designObservational
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

Citations2
Published2013
Admission routes1
Has abstractyes

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