Engineering Heritage: Integrating North America's Largest Façade Retention System with Support of Excavation in the United Bldg. ProjectEngineering Heritage: Integrating North America's Largest Façade Retention System with Support of Excavation in the United Bldg. Project
Bibliographic record
Abstract
The United Bldg. is a landmark project located in the crowded downtown core of Toronto. The 50-storey structure encompasses a city block and incorporates two heritage facades: a nine-storey 1928 Beaux-Arts style structure and a ten-storey 1961 Modern Classical style, both required to be retained in place during construction. Before the inception of this project, a façade retention system (FRS) of ten storeys was unprecedented in the industry. This led to the development of a sophisticated hybrid support system which integrated the FRS with the support of excavation (SOE) for five parking levels to meet the project's complex requirements. The preservation of the historic façades combined with the intricacies of urban construction near sensitive infrastructure, presented significant challenges throughout various stages of the project. This included: controlled demolition of the interior structure while preserving the façade, subsequent installation of secant piles, king piles, and micropiles for both the SOE and FRS, the FRS steel installation and transferring the existing structure’s load onto the newly installed piles, and finally, laterally supporting five levels of excavation while navigating the complexities of working around and beneath the FRS. This paper will provide details of the construction of North America’s largest façade retention system and its successful incorporation into the support of excavation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".