Bibliographic record
Abstract
The use of natural light can improve the quality of indoor environment and also occupants health. In recent years, with an increasing awareness of sustainable development, various innovative methods of integrating daylight into the building have been developed. One such device is the light pipe system. The light pipes are innovative daylighting system that allow the transmission of daylight into the hard-to-reach indoor space. The system consist of mainly three parts. First, a top collector which is mounted on the outside of the roof and gathers skylight and sunlight. Second, light-reflective tube which is coated with highly reflective mirror finish material to transmit the daylight into the diffuser. Third, a diffuser which is installed on the ceiling in the room and spread the daylight into the room. Light pipes have been widely used and researched in many countries such as Australia, America, Canada and Britain. However, despite the significant daylight potential, little work have been carried out in Korea compare to the other countries. In this study, recent lighting technology and application of light pipe system in both Korea and other countries have been compared. For the results, the benefits of each light pipe system and suitable application Korean is also discussed.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".