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Record W4233204654 · doi:10.32920/ryerson.14662632.v1

Re-architecture: means-oriented design

2021· preprint· en· W4233204654 on OpenAlexaff
Arkadiusz Zjawin

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMindsetReuseDemolitionArchitectural engineeringArchitectureResource (disambiguation)Fossil fuelLead (geology)EngineeringIdeal (ethics)Systems engineeringConstruction engineeringComputer scienceCivil engineeringWaste managementPolitical science

Abstract

fetched live from OpenAlex

Depleting fossil fuels and heavy reliance on such energy sources for production of construction materials can render a great deal of disorder in the near future for the architectural, engineering and construction industries. The ideal resource management methods are currently in trial stage, and as much as ‘cradle to cradle’ or ‘closed cycle loop’ are achievable they will have to be accompanied by a different mindset from the designer’s standpoint. Design with reused or superused materials requires a means-oriented approach. With such high levels of residential post construction and demolition waste lies a great opportunity for their direct application (with minor processing), which is currently highly underutilized. Shortcircuiting the material flow and its possibilities for reuse or superuse may lead to a different kind of aesthetics that this thesis seeks to explore.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.220
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations0
Published2021
Admission routes1
Has abstractyes

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