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Record W7162032917 · doi:10.82308/53645

Amortisseur harmonique

2025· dissertation· en· W7162032917 on OpenAlexaboutno aff
Lila Quillin

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicLiterature, Musicology, and Cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsComposition (language)Conjunction (astronomy)Identity (music)

Abstract

fetched live from OpenAlex

Amortisseur Harmonique est une œuvre de dix minutes pour quatuor de saxophones, écrite spécifiquement pour le Quatuor de saxophones Quasar dans le cadre du projet ACTOR 2024 de McGill organisé par le Dr Robert Hasegawa. Parce que ce projet a été créé pour réaliser le potentiel compositionnel des multiphoniques, le but de la pièce est devenu d'extrapoler toutes les caractéristiques musicales qui rendent les multiphoniques uniques, aux niveaux sonore et structurel, et de créer un langage de composition cohérent avec lequel une « histoire » multiphonique pourrait être dit. Il cherche également à explorer comment la multiphonie peut jouer un rôle dans le processus de composition

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)0.002
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: Other · Consensus signal: Other
Teacher disagreement score0.061
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0610.013

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 head0.325
Teacher spread0.302 · 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
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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