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Record W4399351784 · doi:10.1515/9783035627244

Set Pieces

2024· book· en· W4399351784 on OpenAlexaboutno aff
Diamond Schmitt Architects

Bibliographic record

Venuenot available
Typebook
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSet (abstract data type)Computer scienceProgramming language

Abstract

fetched live from OpenAlex

Why does live performance continue to engage us? In a world saturated with recorded entertainment, we seek out the intimacy and immediacy of live music and theater. What is the relationship between design and the experiences, perceptions, and memories it engenders? At its best, architecture, a collection of elements - some apparent, some hidden - shapes and intensifies the process and experience of performance. Set Pieces pairs the words of leading artists and critics with details showcasing the design and inner workings from projects by Diamond Schmitt Architects for some of the world’s most remarkable performing-arts buildings. The book provides an immersive study of fifteen design elements that enhance and transform the perception of performance - and evoke experiences that surpass visual understanding. In-depth documentations of David Geffen Hall at Lincoln Center, New York, Theater an de Parade, Hertogenbosch, National Arts Centre, Ottawa and others A photo essay looks at the backstage world of these famous halls Exploration of the unique typology of performing arts buildings from various angles

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)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.425
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0070.004
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.4250.185

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 head0.040
GPT teacher head0.237
Teacher spread0.197 · 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
Published2024
Admission routes1
Has abstractyes

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