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Record W63467881 · doi:10.5072/zenodo.206485

The Sponge A Flexible Interface

2010· article· en· W63467881 on OpenAlexaff
Martin Marier

Bibliographic record

VenueNew Interfaces for Musical Expression · 2010
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsGestureSpongeContext (archaeology)Computer scienceInterface (matter)Human–computer interactionPerforming artsPleasureElectroacoustic musicEnergy (signal processing)AcousticsArtVisual artsPhysicsArtificial intelligenceGeologyPsychology

Abstract

fetched live from OpenAlex

The sponge is an interface that allows a clear link to be established between gesture and sound in electroacoustic music. The goals in developing the sponge were to reintroduce the pleasure of playing and to improve the interaction between the composer/performer and the audience. It has been argued that expenditure of eort or energy is required to obtain expressive interfaces. The sponge favors an energy-sound relationship in two ways : 1) it senses acceleration, which is closely related to energy; and 2) it is made out of a exible material (foam) that requires eort to be squeezed or twisted. Some of the mapping strategies used in a performance context with the sponge are discussed.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0020.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0470.010

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 head0.017
GPT teacher head0.285
Teacher spread0.269 · 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 designBench or experimental
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

Citations10
Published2010
Admission routes1
Has abstractyes

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