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Assessing the complexity of timber gridshells in architecture through shape, structure, and material classification

2019· article· en· W2915640580 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

VenueBioResources · 2019
Typearticle
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsUniversité du Québec à ChicoutimiUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsArchitectureMateriality (auditing)Architectural engineeringComputer scienceContext (archaeology)OverconsumptionGridConstruction engineeringSystems engineeringEngineeringAestheticsGeologyGeometryMathematics

Abstract

fetched live from OpenAlex

New possibilities offered by recent modelling software allow the design of organic shapes that are appealing to architects and engineers but may encompass serious issues such as an overconsumption of materials. In this context, there is a renewed interest in systems allowing the materialization of curved surfaces such as timber gridshells, which can be defined as shells with their structures concentrated in strips. However, gridshell design becomes highly challenging if complex grid configurations and new material possibilities are combinedly explored with form generations. These upheavals highlight the need for a classification system to seize the potential and the limitations of timber gridshells to address complex geometries. The classification of 60 timber gridshells enables a critical examination in the course of the ceaseless quest for complexity in architecture by evaluating current building possibilities and predict future building opportunities in terms of form, structure, and materiality.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.805
Threshold uncertainty score0.258

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)0.0000.000

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 head0.030
GPT teacher head0.252
Teacher spread0.222 · 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