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Record W2592704199 · doi:10.4995/caa.2017.7301

Nuevas formas de llevar una ópera al teatro. Un caso de estudio. La flauta mágica de la compañía 1927 y de Kosky: animación 2d, nuevas tecnologías digitales y estilo vintage

2017· article· es· W2592704199 on OpenAlexaboutno aff
Vincenzo Sansone

Bibliographic record

VenueCon A de animación · 2017
Typearticle
Languagees
FieldArts and Humanities
TopicArchitecture, Art, Education
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

La ópera, un género que a menudo se asocia al pasado, está más viva que nunca. Gracias a la aportación de directores y experimentadores provenientes del teatro, la ópera se ha convertido en uno de los campos por excelencia para la experimentación contemporánea, sobre todo en relación con el uso de nuevas tecnologías. Una verdadera paradoja. Un ejemplo es la puesta en escena de La flauta mágica de Mozart de la Komische Oper de Berlín, concebida y realizada por la compañía británica 1927 y por el director australiano Barrie Kosky en 2012. Es una representación atípica y extraña que utiliza las nuevas tecnologías del “video project mapping” y, al mismo tiempo, las técnicas de animación 2D —dibujos hechos a mano— con la intención de fusionar estéticas del pasado, sobre todo la del cine mudo y la de los orígenes de la animación, con la contemporaneidad. La intención de este trabajo es analizar la puesta en escena de esta obra en relación con los problemas actuales de la representación de óperas de repertorio.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.013
Scholarly communication0.0080.006
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0230.002

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 head0.019
GPT teacher head0.304
Teacher spread0.285 · 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 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
Published2017
Admission routes1
Has abstractyes

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