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ARCS Architectural Chameleon Skin

2013· article· en· W4298187456 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

VenueeCAADe proceedings · 2013
Typearticle
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInteractivityMateriality (auditing)Computer scienceArchitectureDreamArchitectural geometryHuman–computer interactionComputer graphics (images)MultimediaAestheticsVisual artsArtSoftware

Abstract

fetched live from OpenAlex

Traditionally, interactivity in architecture has been suppressed by its materiality. Building structures that can transform and change themselves have been the dream of many architects for centuries. With the continuous advancements in technology and the paradigm shift from mechanics to electronics, this dream is becoming reality. Today, it is possible to have building facades that can visually animate themselves, change their appearance, or even interact with their surroundings. In this paper, we introduce Architectural Chameleon Skin (ARCS), an installation that has the ability to transform static, motionless architectural surfaces into interactive and engaging skins. Swarm algorithms drive the interactivity and responsiveness of this “virtual skin”. In particular, the virtual skin responds to colour, movements, and distance of surrounding objects. We provide a comprehensive description and analysis of the ARCS installation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score0.661

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.003
GPT teacher head0.154
Teacher spread0.151 · 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