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Design strategies for integration of green roofs in sustainable housing

2015· article· en· W2283976601 on OpenAlexaff
Avi Friedman

Bibliographic record

VenueVITRUVIO - International Journal of Architectural Technology and Sustainability · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Heat Island Mitigation
Canadian institutionsMcGill University
Fundersnot available
KeywordsGreen roofCertificationEnvironmental scienceSustainable designRoofGreen infrastructureUrban heat islandCivil engineeringArchitectural engineeringEnvironmental resource managementGeographySustainabilityEngineeringEcologyMeteorology

Abstract

fetched live from OpenAlex

Green roofs are the integration of plant material and its supporting structures in buildings. Such an approach provides a habitat for local flora and fauna, helps manage storm water, reduces heat demand in winter and the cooling load in the summer, enhances the aesthetic values of dwellings, provides the occupants with comfort and amenities and strengthens environmental responsibility. Because roofs represent approximately 40 percent to 50 percent of the surfaces in urban areas, green roofs have an important role in drainage and as a result water management as well. In fact, when a green roof is installed on 50 percent or more of the roof’s surface, it guarantees 2 points and can contribute 7 additional points toward LEED certification - almost 20 percent of the required rating. This paper classifies green roofs and offers strategies for their integration in residential buildings and examines their benefits, construction principles and applications.

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)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.017
GPT teacher head0.274
Teacher spread0.257 · 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
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

Citations1
Published2015
Admission routes1
Has abstractyes

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