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Record W4402060787 · doi:10.1061/9780784485569.071

Making a Solid Choice: Tunnel Crossing Optimization under the Credit River

2024· article· en· W4402060787 on OpenAlexaff
Neil Harvey, Steven Fradkin, Sarah Lobo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUnderground infrastructure and sustainability
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsLevel crossingComputer scienceEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.967
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.015
GPT teacher head0.274
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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