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Needs of architects regarding digital tools for solar building design

2012· report· en· W4249114294 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsnot available
FundersBundesamt für EnergieProjektträger JülichEnergistyrelsenEnergimyndighetenAustralian GovernmentNational Research Foundation of KoreaBundesministerium für Wirtschaft und TechnologieNational Research FoundationUniversité Laval
KeywordsArchitectural engineeringEngineeringComputer scienceSystems engineering

Abstract

fetched live from OpenAlex

The International Energy Agency (IEA) launched a research project, Task 41: Solar Energy and Architecture, in order to recognise the key role that solar energy will have to play in our future built environment.One of the major findings of this international project is that there is a broad variety of digital tools for solar design, but they are not sufficient to satisfy the requirements of architects in the early design stage.The purpose of the attached letter is to inform you about needs for improved digital tools in architectural design.They were identified through a comprehensive survey of architects in fourteen participating countries and additional interviews with architects in three countries.We are hoping that you will find these results inspiring to start discussions and thought sharing on the future of digital tools for solar design.

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)0.009
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0180.003

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 head0.065
GPT teacher head0.250
Teacher spread0.185 · 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 designQualitative
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

Citations4
Published2012
Admission routes1
Has abstractno

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