Making a Solid Choice: Tunnel Crossing Optimization under the Credit River
Bibliographic record
Abstract
Stantec is working with the Region of Peel on the design of the Lakeshore Road Trunk Sewer to divert flows from GE Booth Water Resource Recovery Facility (WRRF) to the Clarkson WRRF. The sewer will be constructed from Jack Darling Memorial Park approximately 3.3 km, then crossing the Credit River and continuing an additional 1 km to Elmwood Avenue. Understanding the geology at this important crossing location is key in the design and construction of the project, driving the depth of the tunnel and appurtenances. Initial desktop geotechnical information and historic field investigations in the vicinity of the crossing indicated that there was a risk that the subsurface bedrock valley was deeper under and east of the river than to the west, extending under the east riverbank and adjacent public library resulting in mixed face tunneling at the originally planned elevation. Stantec undertook a comprehensive geotechnical field investigation followed by an evaluation of mixed face tunneling vs. deepening the sewer, so that it would remain in rock. The evaluation concluded that deepening the sewer had the most benefit to the Region from an overall construction, cost, and operations viewpoint.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".