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Record W1980830928 · doi:10.1109/pacrim.2013.6625511

STARI: A self tuning auto-monochord robotic instrument

2013· article· en· W1980830928 on OpenAlexaff
Shawn Trail, George Tzanetakis, Leonardo Jenkins, Mantis H. M. Cheng, Duncan MacConnell, Peter F. Driessen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsString (physics)UsabilityComputer scienceField (mathematics)MusicalRoboticsRobotHuman–computer interactionSession (web analytics)Software engineeringArtificial intelligenceVisual artsWorld Wide Web

Abstract

fetched live from OpenAlex

This paper outlines the motivation, design and development of a self-tuning, robotic monochord. This work presents a portable, autonomous musical robotic string instrument intended for creative and pedagogical use. Detailed tests performed to optimize technical aspects of STARI are described to highlight usability and performance specifications for artists and educators. STARI is intended to be open-source so that the results are reproducible and expandable using common components with minimal financial constraints. Because the field of musical robotics is so new, standardized systems need to be designed from existing paradigms. Such paradigms are typically singular in nature, solely reflecting the idiosyncrasies of the artist and often difficult to reproduce. STARI is an attempt to standardize certain existing actuated string techniques in order to establish a formal system for experimentation and pedagogy.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.636
Threshold uncertainty score0.272

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 head0.017
GPT teacher head0.215
Teacher spread0.198 · 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

Citations5
Published2013
Admission routes1
Has abstractyes

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