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Record W1934840894 · doi:10.1016/j.proeng.2015.08.411

Building Energy Consumption in US, EU, and BRIC Countries

2015· article· en· W1934840894 on OpenAlex

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

VenueProcedia Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBRICEnergy consumptionChinaConsumption (sociology)BusinessDeveloping countryInternational tradeEconomicsEconomic growthEngineeringPolitical science

Abstract

fetched live from OpenAlex

This paper presents and discusses data taken from several studies about the building energy consumption in US, EU, and BRIC (Brazil, Russia. India, China) countries. Most of the current researches about energy consumptions deals with statistics in a specific country. However, international comparisons are useful to discover historical, actual, and energy consumption trends. Data presented in reports of the World Bank, the United Nations Environment Program, the Intergovernmental Panel on Climate Change,and the International Energy Agency are compared with national reports as well as with research studies. This analysis shows that the BRIC countries have already overcome the total energy consumption of developed countries, and the expansion of their building stock raises an imperative urgency for energy efficiency in buildings. At the same time, this paper shows that the measures actually adopted in developed countries are insufficient to guarantee a significant reduction in their energy consumption inbuildings.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.216
Teacher spread0.205 · 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