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Record W2742320216 · doi:10.71781/4265

L'utilisation de la percussion comme élément structurant dans l'élaboration d'un langage musical

2016· dissertation· fr· W2742320216 on OpenAlexaboutno aff
Félix-Antoine Coutu

Bibliographic record

VenuePapyrus : Institutional Repository (Université de Montréal) · 2016
Typedissertation
Languagefr
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsPercussionHumanitiesArtPsychologyPhysicsAcoustics

Abstract

fetched live from OpenAlex

Ce mémoire expose le travail effectué durant mes deux années de maîtrise en composition instrumentale à l’Université de Montréal. J’y fais la présentation de cinq pièces ainsi qu’une analyse de chacune d’elles afin de démontrer ma démarche créatrice et mon langage musical. Dans ces cinq pièces, j’ai souhaité approfondir l’écriture pour percussion afin de lui donner une place privilégiée à travers divers ensembles, passant de pièces vocales à une pièce pour quatuor de percussions, jusqu’à des pièces orchestrales. Par l’entremise de la percussion, j’ai mis de l’avant l’aspect rythmique de la musique avec l’utilisation de procédés rythmiques variés comme de la polyrythmie, de l’homorythmie, des changements de métrique, des jeux de pulsation, de la périodicité, etc.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.503
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0110.001
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.234
Teacher spread0.224 · 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 designQualitative
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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

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