Complex fenestration systems: towards product ratings for indoor environment quality
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.
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".