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Record W2578387431 · doi:10.5281/zenodo.1179079

Interactive Lighting In The Pearl: Considerations And Implementation

2015· article· en· W2578387431 on OpenAlexaff
Ian Hattwick, Marcelo M. Wanderley

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2015
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsPearlComponent (thermodynamics)Computer scienceGesturePerforming artsInterface (matter)Human–computer interactionKey (lock)MultimediaController (irrigation)Musical instrumentModalArtificial intelligenceAcousticsVisual arts

Abstract

fetched live from OpenAlex

The Pearl is a multi-modal computer interface initially conceived as an interactive prop for a multi-artistic theatrical performance. It is a spherical hand-held wireless controller embedded with various sensor technologies and interactive lighting. The lighting was a key conceptual component in the instrument's creation both as a theatrical prop and also as an interface for musical performance as it helps to address conceptual challenges and opportunities posed by the instrument's spherical form. This paper begins by providing a brief description of the Pearl and its use as a spherical instrument. We then discuss mapping the Pearl both to generate sound and control its interactive lighting, and identify different strategies for its use. Strategies we identify include feedback regarding performer gesture, information about the state of the instrument, and use as an aesthetic performance component.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0040.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0320.005

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 head0.060
GPT teacher head0.296
Teacher spread0.236 · 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 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

Citations2
Published2015
Admission routes1
Has abstractyes

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