Comparison of the detailed and simplified methods to calculate the apparent sound transmission class for the proposed 2015 National Building Code of Canada
Bibliographic record
Abstract
A new approach to the control of sound transmission is among the changes proposed in the 2015 edition of the National Building Code of Canada (NBCC). The design objective is changing from a minimum Sound Transmission Class (STC) for the wall or floor/ceiling assembly separating adjacent units to a requirement for the Apparent Sound Transmission Class (ASTC) which includes flanking sound transmission. One of the compliance paths in the proposed 2015 NBCC allows for detailed and simplified calculations according to ISO 15712. In support of the proposed 2015 NBCC, the National Research Council Canada has developed a number of guides for the calculation of the direct and flanking STC data for different construction types including concrete and concrete block walls with and without linings. As part of the development of the guides, it was found that the use of the simplified calculations could result in higher values for the direct and flanking STC values compared to the detailed calculations. The higher values put builders at risk of designs which have lower ASTC values than predicted. An alternative method for calculating the direct and flanking STC data for concrete block walls with linings has been proposed which is shown to reduce the risk of overestimating the direct and flanking STC data for the examples considered in this study.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".