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Beyond Smart: Rethink Sustainability for Climate Change

2024· article· en· W4405962295 on OpenAlexaff
Maha Salman, Khalid Sabie, Zeineb Naouar, Samar Sabie

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSustainabilityClimate changeComputer scienceEnvironmental resource managementEnvironmental scienceGeologyEcologyOceanography

Abstract

fetched live from OpenAlex

This research redefines “smart homes” by aligning them with Sustainable Development Goals (SDGs) through the integration of traditional sustainable architectural techniques with modern ICT systems. Typically focused on connectivity, automation, and convenience, conventional smart homes emphasize high-tech solutions for comfort and energy efficiency. However, this study critiques the technological dependency of current smart homes, suggesting a more balanced approach. By incorporating passive design strategies-rooted in traditional architecture that naturally adapts to environmental conditions—with advanced technology, a “smart passive design” paradigm is proposed. This hybrid strategy utilizes case studies of traditional and contemporary houses in hot climates to evaluate building materials and envelope performance. The findings advocate for environmentally and operationally efficient homes, blending time-tested techniques with modern systems, which are more sustainable and resilient in the face of climate change.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score1.000

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)0.0040.001

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 head0.015
GPT teacher head0.260
Teacher spread0.245 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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