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Record W760808722

FROM CONTROLLER TO SOUND: TOOLS FOR COLLABORATIVE DEVELOPMENT OF DIGITAL MUSICAL INSTRUMENTS

2007· article· en· W760808722 on OpenAlexafffund
Joseph Malloch, Stephen Sinclair, Marcelo M. Wanderley

Bibliographic record

VenueThe Journal of the Abraham Lincoln Association · 2007
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Council for the Arts
KeywordsComputer scienceController (irrigation)Graphical user interfaceSound (geography)Development (topology)Musical instrumentMusicalInterface (matter)Human–computer interactionUser interfaceDigital audioControl (management)Peer-to-peerMultimediaWorld Wide WebDigital signal processingAudio signalComputer hardwareOperating system
DOInot available

Abstract

fetched live from OpenAlex

This paper describes the design and implementation of a system for collaborative development of a digital musical instrument mapping layer.System development included the design of a decentralized network for the management of peer-to-peer data connections using Open Sound Control.A graphical user interface for dynamically creating, modifying, and destroying mappings between control data streams and synthesis parameters is presented.

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)0.012
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: Methods · Consensus signal: Methods
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0030.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0120.005

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 head0.021
GPT teacher head0.267
Teacher spread0.246 · 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
GenreMethods

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

Citations23
Published2007
Admission routes2
Has abstractyes

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