Comparison of ASTC results with the calculation performed using the NRC soundPATHS calculator
Bibliographic record
Abstract
The NRC has developed a calculator that predict the apparent Sound insulation, as described in the procedure described in Section 5.8.1.4. or 5.8.1.5. of the 2015 edition of the National Building Code of Canada. Since 1984, MJM Acoustical Consultants has performed a lot of ASTC tests in the field on the huge variety of building structures (wood, steel, concrete, steel/concrete, etc.) and on different types of partitions (wood or steel). Since the 2015 National Building Code of Canada has been enforced in January 2022 in the Quebec province, there will be in increased demand to perform calculation the soundPaths calculator. Therefore, the performance of the calculator compared to real life situations should be assessed. The purpose of this paper is to present several comparison of the ASTC rating measured in the field and the rating provided by the soundPaths calculator using the same partitions compositions and building structure . We will then discuss the difference between the results and proposed some improvements of the NRC SoundPaths calculator.
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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.007 |
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".