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Record W2896825737 · doi:10.1080/00038628.2018.1535423

Aquilomorphism: materializing wind in architecture through ice weathering simulations

2018· article· en· W2896825737 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueArchitectural Science Review · 2018
Typearticle
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsUniversité Laval
FundersFonds de Recherche du Québec-Société et Culture
KeywordsArchitectureArchitectural engineeringAerodynamicsAdaptation (eye)Architectural designProcess (computing)Computer scienceSystems engineeringEngineering design processCivil engineeringEngineeringAerospace engineeringMechanical engineeringGeography

Abstract

fetched live from OpenAlex

This paper proposes a morphological generation method based on the integration of wind forces which leads to organic geometries fostering new spatial experiences and environmental adaptation. It suggests that analogical simulations can generate creative design solutions responding to complex environmental fluxes and can accelerate the design process for architects through tactile explorations of form, matter and spatiality. The aerodynamic design solutions, although contextual, are not deterministic, in the sense that they are reinterpreted to meet the functional needs and constraints of an architectural project. The paper concludes on a sample application that enables practical understanding of the possible uses of the method for architectural and urban design applications.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score0.812

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.277
Teacher spread0.258 · 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