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Record W2090144061 · doi:10.3166/jesa.37.1305-1310

Modélisation physique d'instruments de musique en systèmes dynamiques et inversion

2003· article· fr· W2090144061 on OpenAlexvenueno aff
X. Rodet

Bibliographic record

VenueJournal Européen des Systèmes Automatisés · 2003
Typearticle
Languagefr
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsnot available
Fundersnot available
KeywordsInversion (geology)AcousticsMusical toneNonlinear systemComputer scienceMusicalPhysicsGeologyArtPitch (Music)

Abstract

fetched live from OpenAlex

The self-sustained musical instruments are nonlinear dynamical systems with many regimes of oscillation, even including chaotic ones. Modelling them leads to natural sounds and behaviours. But controlling them is difficult, leading to the question of the inversion: which control for this target sound? The results of the thesis compiled here concern the brass instruments. Three problems are presented: an inversion process for a sub-determined problem, representing lossy curved acoustic waveguides (involving fractional derivatives) with quadripoles including delays, as well as the acoustic radiation. The originality of this work consists of converting mechanical and acoustic problems into automatic ones, which are well-adapted to the simulation (sound synthesis) and the inversion (capture of musical interpretations).

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.555
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
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 head0.023
GPT teacher head0.262
Teacher spread0.239 · 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.

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

Citations7
Published2003
Admission routes1
Has abstractyes

Explore more

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