MétaCan
Menu
Back to cohort
Record W4255328108 · doi:10.3846/13928619.2007.9637813

THE USE OF EXPLORATORY TUNNELS AS A TOOL FOR SCHEDULING AND COST ESTIMATION

2007· article· en· W4255328108 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

VenueTechnological and Economic Development of Economy · 2007
Typearticle
Languageen
FieldEngineering
TopicTunneling and Rock Mechanics
Canadian institutionsBritish Columbia Institute of Technology
Fundersnot available
KeywordsDuration (music)Scheduling (production processes)Computer scienceExcavationMonte Carlo methodEstimationExploratory researchProject managementTrack (disk drive)Operations researchCost estimateEngineeringSystems engineeringOperations managementStatisticsGeotechnical engineering

Abstract

fetched live from OpenAlex

Exploratory tunnels are commonly used for examining the geotechnical and structural aspects of proposed tunnel alignments. This paper explores the utilisation of exploratory tunnels as a project management tool for estimating the cost and duration of construction for the entire project. Data were collected from the Kaponig 2,75 kilometers exploratory tunnel, a part of a double‐track high‐speed railway development in Austria. This knowledge and experience was used to evaluate the risks associated with design details for the final tunnel enlargement (alignment and grade, support requirements and excavation methods). A deterministic model based on Monte Carlo simulation was developed capable of predicting potential outcomes of the total project in terms of cost, duration and their associated probabilities.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.928
Threshold uncertainty score0.268

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 head0.041
GPT teacher head0.225
Teacher spread0.184 · 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