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Record W4220989846 · doi:10.1061/9780784483954.003

Transitioning to the Next Era of Modular Construction: Reconfiguration, Reuse, and Building Stock Agility

2022· article· en· W4220989846 on OpenAlex
Chris Rausch, Sheida Shahi, Aziz Dhamani, Carl T. Haas

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

VenueConstruction Research Congress 2022 · 2022
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsModular designAgile software developmentReuseControl reconfigurationArchitectural engineeringProcess (computing)Stock (firearms)EngineeringAsset (computer security)Computer scienceSystems engineeringConstruction engineeringProcess managementBusinessSoftware engineeringComputer securityMechanical engineering

Abstract

fetched live from OpenAlex

The current era of modular building construction has been largely immutable for the past century in terms of its aspirations, drivers, and objectives. Delivering prompt, cost-effective, and high-quality assets has characterized this era. Yet, a new era is emerging—centered on the post-asset-delivery phase, espoused by prominent circular economy principles. The ability to reconfigure and reuse modular building assemblies in a highly agile manner poses significant opportunities for revolutionizing the environmental and economic impacts of our ever-growing built environment. This paper establishes the groundwork for transitioning toward the next era of modular construction. First, a review of current efforts being made to facilitate this transition is identified. Then, using additional inputs from the industry, a People, Process, Technology (PPT) framework is used to summarize current drivers and constraints. This research provides a cross-sectional analysis of where the modular industry is and how it can transition into its next era.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.038
GPT teacher head0.292
Teacher spread0.254 · 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