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Record W4302064851 · doi:10.52842/conf.acadia.2012.373

Design Ecologies for Responsive Environments: Resonant Chamber, an Acoustically Performative System"

2012· article· en· W4302064851 on OpenAlexfundno aff
Geoffrey Thün, Kathy Velikov, Lisa Sauvé, Wes McGee

Bibliographic record

VenueACADIA quarterly · 2012
Typearticle
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPerformative utteranceComputer scienceAcousticsPhysicsArtAesthetics

Abstract

fetched live from OpenAlex

This paper positions the development and performance of a responsive acoustic envelope system, called Resonant Chamber, within significant discourses in ecology, systems theory and cybernetics. The project is developed through two dominant threads. First, the synthetic design process that entails engaging simultaneous computational and physical investigations which inform each other through various feedback and control regimes - from simulation and testing frameworks to material limits and behaviors to geometric, technological and manufacturing limitations or constraints. Second, the paper elaborates on the system's embedded sensing, communication, feedback and actuation system that transforms its performance to a kinetic, responsive environment that opens up possibilities for active acoustic control, as well as open-ended interaction and play with inhabitants. Within this paradigm, the designer operates through an adaptive mode, between control and the dynamic shaping of possibilities within digital, physical and effective logics, constraints and opportunities.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.006
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.017
GPT teacher head0.228
Teacher spread0.211 · 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 designBench or experimental
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

Citations2
Published2012
Admission routes1
Has abstractyes

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