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Life-Cycle Assessment-Based Environmental Performance Targets for Buildings

2020· book-chapter· en· W3009748514 on OpenAlex
Getachew Assefa

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

VenuePractice, progress, and proficiency in sustainability · 2020
Typebook-chapter
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBenchmarkingArchitectural engineeringLife-cycle assessmentRetrofittingProduct (mathematics)EngineeringSystems engineeringEnvironmental impact assessmentComputer scienceConstruction engineeringEnvironmental resource managementBusinessEnvironmental scienceProduction (economics)

Abstract

fetched live from OpenAlex

The role of targets in delivering meaningful performance improvements for designing new buildings and retrofitting existing building stocks is important. A piecemeal approach of incomprehensive assessments around insignificant changes falls short of achieving deep cuts in impacts. Most of the current assessments are not based on well-defined performance targets. The chapter is centered around exploring the utility of the concept of planetary boundaries for setting well-grounded benchmarking systems in guiding the transformation of the built environment that significantly contributes to the overall environmental impact of the economy. It discusses the role of life cycle assessment, environmental product declarations and product category rules, and how these and relevant standards and guides can be used in tandem with tools and processes used in design offices such as building information modeling. It concludes by charting the need for research on taking concepts such as planetary boundaries to building level benchmarking systems that support better design 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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.832
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.263
Teacher spread0.253 · 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