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Record W2016110579 · doi:10.1145/1180875.1180936

An exploratory analysis of partner action and camera control in a video-mediated collaborative task

2006· article· en· W2016110579 on OpenAlexaff
Abhishek Ranjan, Jeremy Birnholtz, Ravin Balakrishnan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicUsability and User Interface Design
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsZoomTask (project management)Computer scienceAction (physics)Computer visionArtificial intelligenceMotion (physics)Movement (music)Human–computer interactionVideo cameraControl (management)MultimediaEngineering

Abstract

fetched live from OpenAlex

This paper reports on an exploratory experimental study of the relationships between physical movement and desired visual information in the performance of video-mediated collaborative tasks in the real world by geographically distributed groups. Twenty-three pairs of participants (one "helper" and one "worker") linked only by video and audio participated in a Lego construction task in one of three experimental conditions: a fixed scene camera, a helper-controlled pan-tilt-zoom camera, and a dedicated operator-controlled camera. "Worker" motion was tracked in 3-D space for all three conditions, as were all camera movements. Results suggest performance benefits for the operator-controlled condition, and the relationships between camera position/movement and worker action are explored to generate preliminary theoretical and design implications.

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)0.002
metaresearch head score (Gemma)0.020
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 score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.019
GPT teacher head0.274
Teacher spread0.255 · 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

Citations41
Published2006
Admission routes1
Has abstractyes

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