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Record W4230945781 · doi:10.1002/9781118928806.ch2

Concepts Supporting Reuse

2017· other· en· W4230945781 on OpenAlexaff
Mark Gorgolewski

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEnvironmental Science
TopicSustainability and Ecological Systems Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsReuseDeconstruction (building)Component (thermodynamics)Material flow analysisArchitectural engineeringComputer scienceCivil engineeringEngineeringWaste management

Abstract

fetched live from OpenAlex

This chapter discusses some of the concepts and ideas that have been proposed that help facilitate building material and component reuse and that break down some of the barriers. Concepts such as salvageability, secondary use, material flow analysis and urban mining all help to establish a theoretical base for processes that enable buildings to be created using components and materials that have had a previous use. Urban metabolism principles have been employed to analyse the interrelations between environmental, sociological and economic factors of cities to understand the flow of resources through a city, as well as the relationships between urban areas and their hinterlands. The deconstruction (DfD) concept affects the design of all material levels that are accounted for by the technical composition of buildings. In 2005 McDonough and Braungart Design Chemistry (MBDC) launched Cradle to Cradle (C2C), a conceptual framework for assessing and certifying the impact of products, including building components.

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)0.006
metaresearch head score (Gemma)0.009
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: none
Teacher disagreement score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0050.031
Scholarly communication0.0140.025
Open science0.0030.011
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0260.007

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 head0.013
GPT teacher head0.295
Teacher spread0.283 · 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
Published2017
Admission routes1
Has abstractyes

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