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Record W4306796164 · doi:10.34119/bjhrv5n5-257

Análise da eficiência energética da escola classe 01 do Riacho Fundo do Distrito Federal

2022· article· pt· W4306796164 on OpenAlexaff
Tiago Reges da Silva, Caio Frederico e Silva

Bibliographic record

VenueBrazilian Journal of Health Review · 2022
Typearticle
Languagept
FieldEnvironmental Science
TopicUrban Arborization and Environmental Studies
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsPhysicsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Este artigo apresenta os aspectos relativos ao conforto ambiental e a eficiência energética da Escola Classe 01 do Riacho Fundo- DF, classificando a edificação quanto ao seu nível de eficiência energética de forma a aprimorar o potencial do projeto e oferecer maior conforto aos usuários mediante recomendações construtivas e estratégias projetuais. O método foi definido com o propósito de atender ao objetivo proposto de classificar a edificação quanto ao seu nível de eficiência energética. Assim, em busca de classificar o projeto de acordo com a Etiqueta Nacional de Conservação de Energia -ENCE - para edificação comercial, de serviço ou pública a partir dos requisitos contidos no RTQ-C (Regulamento Técnico da Qualidade para o Nível de Eficiência Energética de Edifícios Comerciais, de Serviços e Públicos), o método escolhido foi o método prescritivo disponível no online no site do PBE Edifica. Os dados colhidos demonstram que o projeto escolar apresentado obteve um bom desempenho e pode ser aprimorado por meio de iniciativas simples. Fica evidente a importância em calcular a etiqueta para cada projeto escolar antes da sua implementação.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.367

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.034
GPT teacher head0.298
Teacher spread0.265 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2022
Admission routes1
Has abstractyes

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