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Record W2055966084 · doi:10.7202/1001960ar

L’art du trompe-l’oreille rythmique

2011· article· fr· W2055966084 on OpenAlexvenueno aff
François-Xavier Féron

Bibliographic record

VenueIntermédialités Histoire et théorie des arts des lettres et des techniques · 2011
Typearticle
Languagefr
FieldArts and Humanities
TopicFrench Literature and Poetry
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Un trompe-l’oreille est une entité sonore captieuse dont la principale caractéristique repose sur une disjonction entre sa structuration (comment elle est réalisée) et sa réception (comment elle est perçue). Dans cet article, l’auteur s’intéresse principalement aux patterns résultants qui sont des motifs mélodiques et/ou rythmiques issus de regroupements opérés par la perception sur les stimuli acoustiques provenant d’une ou plusieurs strates sonores ; la production de ces patterns et leurs répercutions auditives sont abordées à travers des exemples musicaux variés comme les polyphonies traditionnelles d’Afrique centrale ou les oeuvres de György Ligeti, Terry Riley et Steve Reich. L’auteur expose également quelques effets rythmiques que seule la précision des ordinateurs autorise, tels que les pulsations infinies ou paradoxales confectionnées par Jean-Claude Risset ou encore le ralentissement perpétuel mis en oeuvre par Autechre dans une de ses compositions. Il s’agit de montrer, à travers ce parcours musical, que des rythmes peuvent en cacher d’autres.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.002

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 head0.035
GPT teacher head0.255
Teacher spread0.220 · 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

Citations4
Published2011
Admission routes1
Has abstractyes

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