Design insights on tubular skylights
Bibliographic record
Abstract
Tubular skylights emerged as alternative products to conventional skylights to deliver daylight without the unwanted solar heat gains, and cover areas not usually covered by windows and skylights. Nowadays, tubular skylights compete with conventional skylights, particularly in commercial and residential buildings. Tubular skylights consist typically of three parts: collector to gather sunlight, pipe to channel sunlight downward, and ceiling diffuser to diffuse light to the indoor space. The collector is usually hemispheric and made up of clear glazing. The collector may also include some devices to enhance the lighting output of the skylight, especially at low sun altitude angles. The pipe is made up of an Aluminium sheet with highly reflective interior lining. Materials with reflectivity of 99% are commercially available. The diffuser is hemispheric or flat with translucent (opal) or clear glazing. Translucent glazing performs well in light diffusion, but is not efficient in light transmission. On the other hand, clear glazing is efficient in light transmission, but usually requires lenses for light diffusion. Due to this product complexity, prediction of the skylight performance has always been a difficult task. Although some tentative design guides have been proposed by researchers and some skylight manufacturers, tubular skylights still lack some design insights that would help building designers or architects to properly select and deploy skylight products to achieve the desired energy savings.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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.
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".