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Record W1980560039 · doi:10.1145/2030441.2030467

EMVIZ

2011· article· en· W1980560039 on OpenAlexaff
Pattarawut Subyen, Diego S. Maranan, Thecla Schiphorst, Philippe Pasquier, Lyn Bartram

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsComputer scienceMovement (music)VisualizationHuman–computer interactionContext (archaeology)Process (computing)Artificial intelligenceMultimediaComputer visionAestheticsArt

Abstract

fetched live from OpenAlex

This paper describes the design of an interactive visualization prototype, called EMVIZ, that generates abstract expressive visual representations of human movement quality. The system produces dynamic visual representations of Laban Basic-Efforts which are derived from the rigorous framework of Laban Movement Analysis. Movement data is obtained from a real-time machine-learning system that applies Laban Movement Analysis to extract movement qualities from a moving body. EMVIZ maps the Laban Basic-Efforts to design rules, drawing parameters, and color palettes for creating visual representations that amplify audience ability to appreciate and differentiate between movement qualities. EMVIZ was demonstrated in a gallery context. The audience reported that the system produces evocative and meaningful visual representations of Laban Basic-Efforts. This paper describes the metaphoric mapping process used to design and implement the visualization system and discusses the aesthetics of the resulting visual style.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.915
Threshold uncertainty score0.227

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)0.0000.000

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 head0.042
GPT teacher head0.218
Teacher spread0.176 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations13
Published2011
Admission routes1
Has abstractyes

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