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Record W4366077128 · doi:10.56698/filigrane.1312

L’art des drones et des nappes synthétiques (synth pads) 

2022· article· fr· W4366077128 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFiligrane · 2022
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsMusée de la Civilisation
Fundersnot available
KeywordsDemonArtHumanitiesLiterature

Abstract

fetched live from OpenAlex

Troisième long-métrage du binôme formé par le Danois Nicolas Winding Refn et Cliff Martinez après Drive et Only God Forgives, The Neon Demon explore le monde impitoyable de la mode à Los Angeles à travers le parcours de Jesse (Elle Fanning), une jeune femme à la beauté pure et irrésistible. Pour ce film qui marque selon le compositeur l’« aboutissement d’une collaboration », Cliff Martinez continue de proposer des partitions intégralement électroniques, entre beat techno et trance new age, démontrant un art consommé dans le maniement d’un matériau suscitant généralement peu d’intérêt, les synth pads ou « nappes synthétiques ».En l’absence quasi totale de thèmes mélodiques, la narrativité musicale se fonde sur des motifs sonores et des thèmes harmoniques élaborés à partir de drones et de nappes synthétiques. En pensant sa musique dès sa conception pour s’intégrer au soundscape global du film – « motif du diamant » possédant une version bruitiste et une version musicale, discrétion des points d’entrée musicaux – voire en la concevant elle-même comme un soundscape – renforcement de la composante bruitiste, intégration de drones bruitistes et de bruits dans la composition –, Cliff Martinez s’affirme comme un maître de la « soundscape score ».

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.520
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.244
GPT teacher head0.322
Teacher spread0.079 · 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