MétaCan
Menu
Back to cohort
Record W1992591864 · doi:10.1016/j.egypro.2012.11.138

Achieving Solar Energy in Architecture-IEA SHC Task 41

2012· article· en· W1992591864 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

VenueEnergy Procedia · 2012
Typearticle
Languageen
FieldEnergy
TopicSolar Thermal and Photovoltaic Systems
Canadian institutionsToronto Metropolitan UniversityUniversité Laval
FundersEnergistyrelsen
KeywordsRenewable energyArchitectureTask (project management)Architectural engineeringEngineeringSolar energySystems engineeringProcess (computing)Computer scienceEngineering managementGeographyElectrical engineering

Abstract

fetched live from OpenAlex

Despite the wide diversity of available solar technologies, solar energy systems are still not considered as main stream technologies in building practice. This may be attributed to several factors such as lack of awareness and knowledge among architects, lack of tools supporting the design process, and lack of solar products designed for building integration. In order to address these issues, the IEA SHC Task 41 “Solar Energy and Architecture” was carried out during 2009 to 2012. The main aim was to promote the use of solar energy systems within high quality architecture. The main expected outcome is an increased use of solar energy in buildings, reducing the non-renewable energy use and GHG emissions. Fourteen countries participated. The work was organized in three subtasks: A) integration criteria and guidelines, B) tools and methods for architects, and C) case studies and communication guidelines. This article presents an overview of the Task's activities and results. The results include an inventory of computer tools, a literature review, a survey on solar systems perception and use by architects, a survey on needs regarding tools for solar design, recommendations for computer tool developers and different guidelines for solar product developers and architects. Finally an extensive collection of more than 250 case studies with integration of solar systems was evaluated and resulting in the online publication of around 65 selected cases demonstrating inspiring solar architecture. The results of Task 41 are also currently being disseminated through seminars and workshops for building professionals.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.011
GPT teacher head0.211
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