Complex fenestration systems: towards product ratings for indoor environment quality
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.
Bibliographic record
Abstract
Complex fenestration systems (CFS) include windows featuring complex glazing such as translucent and transparent insulation, solar control films, patterned or decorative glass, in-between pane shades, etc. CFS are believed to exhibit superior energy performance, but may have adverse effects on environmental features important for building-occupant satisfaction requirements such as the outdoor view (connection to outside), indoor view (feeling of privacy), luminance (major factor for discomfort glare), and light diffusion quality (relates to uniformity of illuminance on work plane). This article is part of a larger effort to rate complex fenestration systems for energy performance and indoor environment quality (IEQ). In the end, IEQ ratings must be derived from direct studies of how building occupants perceive the indoor environment conditions created by the installed fenestration product. As a first step, this work tackles the theoretical development of new metrics to rate CFS with regards to IEQ, namely the view impairment index, luminance index, and light diffusion quality index. The new indices are applied to some typical CFS, namely a diffuse window, and a clear window combined with an interior shading screen, and integrated perforated Venetian blinds. The results show that the diffuse window may increase the luminance by more than 100% under clear sky conditions when compared with a clear window with a similar light transmittance. White colored Venetian blinds may increase the window luminance by up to 50% and reduce the outdoor view by up to 66% as compared with a clear window with a similar light transmittance.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it