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Record W2592509128

Evaluating Green and Blue Roof Opportunities in Canadian Cities

2017· dissertation· en· W2592509128 on OpenAlexaboutno aff
Richard W. Hammond

Bibliographic record

VenueUWSpace (University of Waterloo) · 2017
Typedissertation
Languageen
FieldEnvironmental Science
TopicUrban Heat Island Mitigation
Canadian institutionsnot available
Fundersnot available
KeywordsGreen roofRoofGeographyArchitectural engineeringRegional scienceEnvironmental planningCivil engineeringCartographyEngineering
DOInot available

Abstract

fetched live from OpenAlex

Flat roof surfaces represent a significant proportion of urban areas and perform a variety of functions for buildings, with a corresponding variety of impacts on the urban environment and its infrastructure. One of the most important flat roof functions is the collection and discharge of rainwater, which especially during storms has a substantial impact on municipal sewer systems and the water bodies into which they discharge. The use of vegetated, or ‘green’, roofs has become a prevalent strategy for mitigating the impacts of stormwater runoff from flat roof surfaces in urban areas, including in Canadian cities, and has received a significant amount of research attention. There is also a variety of ‘blue’ roof strategies that involve detention or retention of rainwater, either on roof surfaces or in cisterns. These approaches have received considerably less research attention, particularly for large buildings. \n \nThis study compares the performance of green and blue roof systems, based on their effectiveness as stormwater management strategies, as well as their life cycle energy, carbon dioxide, and economic impacts. The more qualitative attributes of green and blue roofs are also explored, as well as their compatibility with other rooftop technologies including solar photovoltaic panels, solar thermal hot water heating systems, and high albedo membranes. In this context, the apparently under-appreciated opportunities for rainwater harvesting and reuse inside buildings are examined for a variety of large building types in three Canadian cities with different climatic conditions: Calgary, Alberta, London, Ontario, and Halifax, Nova Scotia. \n \nFrom this investigation, recommended decision criteria are developed for the selection of the most appropriate green or blue roof strategies depending on the characteristics of a particular building project, including its size, occupancy, geographic location, and urban context. Limitations of this study’s methods, as well as issues in need of further research, are also discussed.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.586

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.008
Science and technology studies0.0050.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.038
GPT teacher head0.238
Teacher spread0.200 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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