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Record W2060935065 · doi:10.1021/es0517522

Comparative Life Cycle Assessment of Standard and Green Roofs

2006· article· en· W2060935065 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

VenueEnvironmental Science & Technology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Heat Island Mitigation
Canadian institutionsImpactUniversity of TorontoEnvironment and Climate Change Canada
Fundersnot available
KeywordsGreen roofRoofEnvironmental scienceReflective surfacesLife-cycle assessmentUrban heat islandCooling loadHeat fluxEnvironmental engineeringMeteorologyCivil engineeringEngineeringHeat transferAir conditioningGeographyProduction (economics)

Abstract

fetched live from OpenAlex

Life cycle assessment (LCA) is used to evaluate the benefits, primarily from reduced energy consumption, resulting from the addition of a green roof to an eight story residential building in Madrid. Building energy use is simulated and a bottom-up LCA is conducted assuming a 50 year building life. The key property of a green roof is its low solar absorptance, which causes lower surface temperature, thereby reducing the heat flux through the roof. Savings in annual energy use are just over 1%, but summer cooling load is reduced by over 6% and reductions in peak hour cooling load in the upper floors reach 25%. By replacing the common flat roof with a green roof, environmental impacts are reduced by between 1.0 and 5.3%. Similar reductions might be achieved by using a white roof with additional insulation for winter, but more substantial reductions are achieved if common use of green roofs leads to reductions in the urban heat island.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.272
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.236
Teacher spread0.230 · 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