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Assembly restoration framework for modelling circular building strategies

2025· article· en· W4409875585 on OpenAlexaff
Adama Olumo, Costa Kapsis, Carl T. Haas

Bibliographic record

VenueResources Conservation and Recycling · 2025
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCircular economyEngineeringEnvironmental scienceConstruction engineeringArchitectural engineeringWaste managementBusinessEnvironmental resource managementCivil engineeringEnvironmental planningEcologyBiology

Abstract

fetched live from OpenAlex

Building renovations often focus on new building components, neglecting the potential of refurbished or reclaimed resources. This study develops a circular restoration framework to model different strategies for the end-of-life management of building assemblies. These strategies include: (1) Partial replacement – substituting parts of an old assembly with new parts, (2) Direct reuse–making no changes to the existing assembly, (3) Partial refurbishment – restoring old parts without undergoing a re-manufacturing process, and (4) Full replacement – purchasing a new assembly. The value of the framework is demonstrated through a window assembly example that assesses operation and embodied energy impacts of the different restoration strategies. The results show that integrated approaches, such as partial replacement and partial refurbishment, offer opportunities to mitigate tradeoff factors like embodied and operational energy. The Assembly Restoration Framework (ARF) facilitates comparative assessment of circular strategies, enhancing circular practices.

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 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: none
Teacher disagreement score0.589
Threshold uncertainty score0.451

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 head0.021
GPT teacher head0.259
Teacher spread0.239 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations1
Published2025
Admission routes1
Has abstractyes

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