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Record W2809486160

Avaliação de edifícios no Brasil: da avaliação ambiental para avaliação de sustentabilidade

2008· article· pt· W2809486160 on OpenAlex
Vanessa Gomes da Silva, Maristela Gomes da Silva, Vahan Agopyan

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typearticle
Languagept
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilitySustainable developmentEnvironmental impact assessmentBusinessEnvironmental planningEnvironmental resource managementPolitical scienceGeographyRegional scienceEconomic growthEnvironmental protectionWelfare economicsEconomicsEcology
DOInot available

Abstract

fetched live from OpenAlex

Governmental agencies, research institutions and private sector worldwide have largely encouraged the development of research concerned with the reduction of the environmental impacts of buildings. The concept of life cycle analysis has supported the development of methodologies for environmental assessment of buildings that emerged in the 90’s as part of the strategies for the attainment of local environmental targets set at the ECO’92. Each European country, as well as the United States, Canada, Australia, Japan and Hong Kong, has its own assessment system. All of them deal exclusively with the environmental dimension of building sustainability. This paper presents and briefly compares the main initiatives on environmental assessment and rating systems, emphasizing the inadequacy of simply importing existing methods based on their success in countries with latitudes, social, economic and environmental conditions far different from those in Brazil. Finally, it discusses the expectations regarding the participation of Brazil in the Green Building Challenge, as well as the strategies to develop research in this field in this country.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.567
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.031
GPT teacher head0.279
Teacher spread0.248 · 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