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Record W4243018995 · doi:10.1504/ijde.2021.113249

Coherence of interior and exterior formal qualities in parametrically designed buildings

2021· article· en· W4243018995 on OpenAlexaff
Morteza Hazbei, Carmela Cucuzzella

Bibliographic record

VenueInternational Journal of Design Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsConcordia University
Fundersnot available
KeywordsArchitectural engineeringParametric statisticsArchitectureCoherence (philosophical gambling strategy)Space (punctuation)Envelope (radar)Computer scienceSet (abstract data type)Parametric designInterior designEngineeringMathematicsVisual artsTelecommunications

Abstract

fetched live from OpenAlex

Parametrically designed buildings often have spectacular exterior forms, quasi-sculptural, that catch the eye of the passers by. However, the indoor space design of parametric architecture has received less attention due to over emphasis on exterior aesthetic requirements. This may lead to superficial aesthetics where the quality of the indoor space is not compatible with the outer building envelope. This paper seeks to highlight the importance of coherency between these two parts of parametrically designed buildings. To do this, we conducted a two-step survey with architecture students where we first presented a set of different views of indoor and outdoor spaces of some parametric buildings. They were asked to match the images of the interior spaces to images of the exterior facades. In the second step, students were asked to evaluate each building by their formal criteria (specifically the coherence of the façade and indoor space) for parametrically designed projects in order to identify if a gap existed between the two aesthetics.

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)0.011
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.232
Teacher spread0.220 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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