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Record W4244296802 · doi:10.1002/geot.202100015

Advanced design of large cavern intersections in soft ground without conventional bar reinforcement

2021· article· en· W4244296802 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGeomechanics and Tunnelling · 2021
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsPublic Health Ontario
Fundersnot available
KeywordsShotcreteReinforcementExcavationBar (unit)Geotechnical engineeringStructural engineeringEngineeringGeology

Abstract

fetched live from OpenAlex

Abstract The design of three mined stations in Toronto as part of the Eglinton Crosstown Light Rail Project involved several intersections of large tunnels situated in the heterogenous, water‐bearing glacial till deposits. The most challenging openings, 220 m 2 each, were formed in the two sides of the 18 m high cross‐cut tunnels to allow the excavation of the 18 m wide platform caverns. A key objective for the design was the optimization of the tunnel shapes and the advanced simulation of the fibre reinforced shotcrete properties, to allow these openings in the initial tunnel linings to be achieved without conventional bar reinforcement or thickenings, thus simplifying and accelerating the construction, whilst reducing health and safety risks. Advanced numerical analyses were utilized to simulate the staged excavation and support steps introducing advanced material models that accounted for the non‐linear behaviour of both soil and structural elements. The end product was an optimized design of the tunnel linings with synthetic fibre reinforced shotcrete without conventional reinforcement that was successfully implemented in the construction.

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.

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 score0.937
Threshold uncertainty score0.471

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.209
Teacher spread0.199 · 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