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Record W4396709939 · doi:10.11159/icgre24.112

Geotechnical Challenges and Technical Solutions for Settlements Reduction for the New Access Gallery to the Ceneri base Tunnel (Switzerland)

2024· article· en· W4396709939 on OpenAlexvenueno aff
Gianluca Di Bella, Alessandro Flematti, M. Falanesca, Filippo Gianelli, D. Merlini

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBase (topology)Human settlementReduction (mathematics)Geotechnical engineeringCivil engineeringEngineeringForensic engineeringGeologyWaste management

Abstract

fetched live from OpenAlex

This paper deals with the main results of an extensive monitoring campaign carried out to quantify the vertical displacement due to the installation of some pre-loads to be realized before the construction of an artificial tunnel.As part of the "Sigirino access tunnel" project, this concrete structure will be realized on highly deformable, saturated silty so that some relevant settlements are expected, therefore they must be minimized to satisfy Serviceability Limit State requirements.Monitoring results are compared with outcomes given by bidimensional finite element analysis, to provide the basis for an appropriate design of the tunnel and to predict the stress-strain response of the structure itself during its work life.

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: Empirical
Teacher disagreement score0.340
Threshold uncertainty score0.625

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 head0.015
GPT teacher head0.220
Teacher spread0.206 · 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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