Bibliographic record
Abstract
Health-care facilities include many non-clinical office spaces for administrative staff; the role of acoustics in these spaces has been underexplored. This paper discusses the acoustical part of a study of indoor environmental quality (IEQ) in 17 healthcare office facilities. Physical acoustical measurements were made in six types of rooms, some with sound-masking systems, to determine the acoustical characteristics, assess their quality, relate them to the building designs, and develop prediction models. Background-noise levels were measured in the occupied buildings. In the unoccupied buildings, measurements were made of reverberation times, and “speech” levels needed to calculate speech intelligibility indices for speech intelligibility and speech privacy. In open offices, sound-level reductions per distance doubling (DL2) were measured. Noise isolations of internal partitions of different designs (double-plasterboard construction, modular or built in-situ, rising to the suspended ceiling or to the floor-ceiling slab, without and with doors, different amounts of glass) were measured. The acoustical characteristics were compared to design criteria to evaluate their acceptability. The results are presented, and are related to room type and partition design. An empirical model for predicting partition noise isolation, developed using regression techniques, is discussed. The knowledge gained from this study informs the decision-making of designers and facilities management for upgrades and future design projects.
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How this classification was reachedexpand
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".