A unique application of Diaphragm Wall to facilitate the excavation of New River Channel on The Port Lands Flood Protection and Enabling Infrastructure Project in Toronto, Ontario
Bibliographic record
Abstract
The Port Lands in Downtown Toronto is a vast waterfront area that has been long remained undeveloped. This is due to the dual challenges of soil contamination resulting from decades of industrial activities and high flooding potential from the nearby Don River. The Port Lands Flood Protection and Enabling Infrastructure Project (PLFP) seeks to unlock the development potential of this strategic downtown land. This initiative also simultaneously mitigating flood risks for the Port Lands and surrounding areas. The project involves the creation of a new river channel through the existing Port Lands to redirect floodwaters into the inner harbor and Lake Ontario. This new river channel excavation is protected by three dam liked plug walls which isolate the lake water from entering the excavation. Given the industrial contamination in the soil, the installation of a permanent cut-off wall along the new river alignment is also imperative to isolate contaminants from migrating into the future river channel. The west plug wall is positioned at the westernmost point of the river channel excavation and directly adjacent to Lake Ontario. The innovative use of a diaphragm wall technique to construct the west plug wall allow the wall to serve as a dock wall, dam, excavation support, cut-off wall, and load-bearing element throughout the different stages of the river excavation. This paper provides a comprehensive overview of the design and installation of the west plug wall. It provides valuable insights into the practical application of diaphragm walls and how it helps deliver this complex urban flood protection and infrastructure projects.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".