Bibliographic record
Abstract
An extensive series of measurements of airborne and impact sound insulation on joist floors of various types was recently completed at NRC. About 190 floors with different joist types, subfloors, ceiling types, ceiling support systems, and type and thickness of sound absorber were constructed and sound insulation measured to frequencies lower than required by standards. The joist types comprised solid wood, wood trusses, I-joists, and steel joists. Glass, rock, and cellulose fiber sound-absorbing material were used. Three concrete slabs were included in the series and a few of the joist floors had concrete toppings installed. Impact devices used on the floors included the standard ISO/ASTM E492 tapping machine, a walker, a JIS 1419 tire impactor, and two experimental rubber balls. The impact measurements provide an extensive, consistent set for examining alternative impact tests and possible modifications to standard tests using the ISO tapping machine. Correlations among the sound levels from the different impactors show that levels from the ISO tapping machine correlate well with those from a walker at low frequencies, although the spectra are quite different in shape. An overview of the data and the prospects for a new test method and rating system will be presented.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".