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Record W2365855204

Landscape Value of Green Roofs

2010· article· en· W2365855204 on OpenAlexaboutno aff
Bao Jia-sheng

Bibliographic record

VenueJiangsu Construction · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicRemote Sensing and Land Use
Canadian institutionsnot available
Fundersnot available
KeywordsGreen roofUrbanizationLegislationChinaEnvironmental planningNoise pollutionGeographyUrban landscapeEnvironmental protectionValue (mathematics)Civil engineeringUrban heat islandRoofEnvironmental engineeringEnvironmental scienceEngineeringEconomic growthPolitical scienceLawEconomicsMeteorologyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Recently,with the acceleration of the process of urbanization in China.Environmental problems are becoming more and more apparent.Such as heat island effect,air pollution,sewage overflow,noise pollution those seem to be a common problem in the process of urban development.However,the emergence of the green roof can play a positive role on solving these urban environmental problems and which accepted by designers,developers and environmental experts.Green roof is not a new concept of environmental protection.In the 60s of last century,this word was appeared in United States,Britain,Germany,Canada and other countries.By now Switzerland,Austria,Germany,Japan and other advanced countries all make green roofs mandatory by legislation.So this paper will analyse and summarize the characteristics and category of green roof to elaborate the value of different types of green roofs that contribute to urban landscape.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.182
Teacher spread0.177 · 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
Published2010
Admission routes1
Has abstractyes

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