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Record W1971857760 · doi:10.1260/1478-0771.9.2.187

Aviva Stadium: A Case Study in Integrated Parametric Design

2011· article· en· W1971857760 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

VenueInternational Journal of Architectural Computing · 2011
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsDalhousie University
Fundersnot available
KeywordsStadiumParametric statisticsIterative designParametric designComputer scienceProcess (computing)ConversationArchitectural engineeringWork (physics)Design processIterative and incremental developmentSystems engineeringOperations researchIndustrial engineeringEngineeringWork in processSoftware engineeringOperations managementSociologyMechanical engineeringMathematics

Abstract

fetched live from OpenAlex

The nature of large complex buildings requires specialized skills across a multi-disciplinary team and high levels of collaboration and communication. By taking a parametric approach to design and construction, high quality results can be delivered on budget on time. This type of approach facilitates the opportunity for design teams to work in an iterative manner. A parametric model reduces the time associated with complex design changes while providing a centralized method for coordinating communication. In this paper the recently completed Aviva Stadium is used to illustrate the ways in which these benefits manifest themselves on built work. The authors identify the moments in the design and construction process that truly justify the effort in implementing a parametric approach. By approaching design in this way a “design conversation” can take place between parties involved, resulting in a better building.

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 score0.638
Threshold uncertainty score0.426

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.041
GPT teacher head0.264
Teacher spread0.223 · 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