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Record W2151900156 · doi:10.5555/564124.564347

Design, development and application of soil transition algorithms for tunneling using special purpose simulation

2001· article· en· W2151900156 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.

Bibliographic record

VenueWinter Simulation Conference · 2001
Typearticle
Languageen
FieldEngineering
TopicTunneling and Rock Mechanics
Canadian institutionsUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsBoreholeQuantum tunnellingAlgorithmComputer scienceWork (physics)Tunnel constructionGeotechnical engineeringEngineeringMechanical engineeringMaterials science

Abstract

fetched live from OpenAlex

In tunnel construction, the vertical boreholes only show the soil types that are available in the borehole locations. The soil profiles between the boreholes are uncertain and assumed by practitioners for construction purposes. The productivity of the tunnel construction work is therefore affected by adverse soil conditions. The successful implementation of a special purpose tunneling simulation tool identified that the modeling of uncertainties such as soil conditions could provide better results. This paper presents new modeling algorithms to predict the transition of soils between the boreholes along the tunnel path. The use of transitional probabilities enables to predict the transition points. The various scenarios of the mixed phases of soils are considered for modeling within the special purpose tunnel simulation template. Application of the simulation for modeling algorithms to a past construction project proved that this modeling algorithms provide a logical and an accurate prediction of the tunnel advance rate.

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 score0.790
Threshold uncertainty score0.540

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 head0.062
GPT teacher head0.280
Teacher spread0.218 · 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