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Record W4388865328 · doi:10.4324/9781003356950-22

Yellow + Blue

2023· book-chapter· en· W4388865328 on OpenAlexaboutno aff
Zenovia Toloudi, Pallavi Swaranjali

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldChemistry
TopicDye analysis and toxicity
Canadian institutionsnot available
Fundersnot available
KeywordsArt

Abstract

fetched live from OpenAlex

In an era when architecture and cultural experiences often occur in virtual sites, Zenovia Toloudi’s Yellow + Blue is conceived as a labyrinth experienced in a public space. It is presented through its life at the campus of Carleton University in Ottawa, as well as theoretically through a glossary of terms defining architectural apparatuses. An architectural apparatus can be an individual element with various forms, materials, textures and perforations, an opening and a threshold, a design of scales, geometries, proportions and dimensions or a strategic positioning of a building to produce an effect in the eyes of the beholders. Architectural apparatuses intervene in buildings to transmit light or re-create an image interrupting and revealing hidden or overlooked nuances of daily routine through the production of ever-changing phenomena or to produce an illusion of infinity in an interactive futuristic model. Through experiment and experience, certain ideas prevail about architectural apparatuses: they are non-representational artifacts; they become portals for phantasmagoria; they disrupt spatial homogeneity; they recalibrate the senses and cognitive abilities of viewers; they displace temporarily one’s image in relation to the surroundings; they are theatrical, literal and temporal; they become transitional objects or communicative devices; and they become co-producers of space.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.628
Threshold uncertainty score0.992

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)0.0610.009

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 head0.025
GPT teacher head0.226
Teacher spread0.201 · 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; both teacher heads agree on what is shown here.

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
Published2023
Admission routes1
Has abstractyes

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