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Record W2886856150 · doi:10.1201/9781315690889-19

Sustainability of office buildings

2017· article· en· W2886856150 on OpenAlexaboutno aff
Sofia Dermisi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityBusinessArchitectural engineeringEngineering

Abstract

fetched live from OpenAlex

Sustainability has been pursued by owners of office buildings with varying frequency since the 1990s, as owners and managers seek improvements in capital and operational costs, return on investment (ROI), retrofit length, and tenant attractiveness/comfort, among a variety of building specific benefits. The millennial generation of workers seems to be more socially and sustainability conscious than generation X and the baby boomers, therefore further solidifying the adoption of sustainable practices in the workplace. A building’s sustainability performance can be benchmarked based on recent building codes in certain communities or assessed and certified on a more holistic basis by private rating systems certifying buildings worldwide. Prominent holistic building sustainability assessment systems with worldwide outreach include: Leadership in Energy and Environmental Design (LEED) by the US Green Building Council (USGBC) – based in and dominating the USA market; Building Research Establishment Environmental Assessment Method (BREEAM) – based in and dominating the UK; and Green Globes – based in Canada and the USA.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.010
GPT teacher head0.261
Teacher spread0.251 · 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 designNot applicable
Domainnot available
GenreOther

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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