International Survey About Digital Tools Used by Architects for Solar Design
Bibliographic record
Abstract
This report forms part of IEA-SHC Task 41: Solar Energy and Architecture, specifically Subtask B: Methods and Tools for Solar Design. After a literature review of former studies made between 1993 and 2011, the international survey Design Process for Solar Architecture, conducted in 2010 within Task 41 is presented and analyzed. Professionals in 14 countries were contacted and questioned about their use of digital tools for solar design and related themes, such as, barriers for the use of digital tools or their design process. In addition, general data concerning the firm (size, type of buildings) and personal facts (age, experience, profession) was collected. The response rate was less than hoped; nevertheless, this report points out that there is a high awareness of the importance of solar energy use in buildings, but that there are still a number of barriers to the widespread application of digital tools during the design process. The survey affirms results of former investigations by others presented in literature review that widely accepted solar design software packages adequate for use by architects in the early design phase are still lacking. The identification of opportunities and obstacles, special requirements expressed by professionals and suggestions for improvements will help formulate the next program of work, which will involve the development of guidelines for both professionals and software tool developers in order to support design methods and enhance the use of solar energy in building projects.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".