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Record W2794346688

The prairie above: a regional investigation into the green roof technology and application

2012· article· en· W2794346688 on OpenAlexaboutno aff
Shauna MacArthur

Bibliographic record

VenueMspace (University of Manitoba) · 2012
Typearticle
Languageen
FieldEngineering
TopicSustainable Design and Development
Canadian institutionsnot available
Fundersnot available
KeywordsGreen roofGeographyEnvironmental scienceArchitectural engineeringRoofEngineeringArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Issues associated with urban development such as the urban heat island effect, loss of habitat, increased areas of impervious surfaces leading to storm water management concerns are well known. Many designers, engineers and policy creators are sensitive to these issues creating positive change by implementing alternatives to traditional development. Although, the concept of green roofs is not new to the prairies, modern development of this technology has not been fully embraced. Surrounded by concerns of efficacy and longevity here in the harsh northern prairie climate, green roof development and implementation has been slow. The objective of this practicum is to determine what green roof system and what vegetation of the short grass / fescue prairie and mix grass prairie would succeed in a green roof setting. Determining the appropriate planting palette and growth medium depth for the Canadian Prairies is essential for the development of the green roof industry locally.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
Threshold uncertainty score0.376

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.008
GPT teacher head0.172
Teacher spread0.164 · 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
Published2012
Admission routes1
Has abstractyes

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