Acoustic performance of green buildings: a post-occupancy evaluation
Bibliographic record
Abstract
Awareness about large energy consumption and global warming risks has encouraged many initiatives for sustainability and energy consumption reduction. As buildings account for large portion of energy consumption worldwide many initiatives address the issue of the sustainability of buildings. There is an increasing trend toward green buildings among building industry in general. This is led mostly by third party non-governmental initiatives such as the US Green Building Council and its LEED green building rating system which has become one of the leading green building initiatives worldwide. Green building rating schemes require buildings to be environmentally friendly, resource and energy efficient and healthy places to live and work. Yet the quality of the buildings certified according to commercially available green building schemes is sometimes questioned. Many studies have found discrepancies between the designed and the actual performance of the certified green buildings. Furthermore, acoustic performance is one of the aspects quite often overlooked by the schemes. In the buildings, acoustics sometimes represents conflicting situations with other aspects of buildings performance such as thermal, or indoor air quality, or even lighting. Therefore it is very important to include the examination of acoustic performance alongside other aspects for a high quality green building. While providing an overview of the common problems reported on the acoustics of green buildings, this paper compares the results of a post-occupancy evaluation of a number of green and conventional buildings.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".