Bibliographic record
Abstract
Because it is a complex, multi-degree-of-freedom system, the success of a building isolation installation depends on careful selection of a number of design factors. The new Toronto Opera House, the Four Seasons Centre for the Performing Arts, opened in June 2006, is located directly adjacent to a surface light rail trackway and to a subway rail transit system. The results characterized as "the quietest Opera House in the world" demonstrate that groundborne noise and vibration is not a factor precluding the use of a noisy site for a noise-sensitive facility. Measurement of the existing groundborne noise provided the basis to determine the required noise reduction. Very stiff and massive foundation elements with stiff and massive structure directly above the isolation bearings allows the isolation design to be simplified to a single-degree-of-freedom system for deriving the performance of the isolation at low frequencies. Natural rubber bearings with thickness adjusted to achieve a specific amount of insertion loss for the structure-borne noise can be used to determine the expected performance at frequencies above 50-80 Hz. Isolation system design parameters for the new 2000-seat Opera House Performance Hall and graphical results from vibration and noise projections and tests are 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".