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Record W2128383083 · doi:10.1061/9780784413616.216

Estimating Potential Cost Savings from Implementing an Innovative TBM Guidance Automation System

2014· article· en· W2128383083 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

VenueComputing in Civil and Building Engineering (2014) · 2014
Typearticle
Languageen
FieldEngineering
TopicTunneling and Rock Mechanics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAutomationContext (archaeology)Reliability (semiconductor)Cost estimateIdentification (biology)CrewComputer scienceReliability engineeringProductivityRisk analysis (engineering)Field (mathematics)EngineeringSystems engineeringBusinessAeronautics

Abstract

fetched live from OpenAlex

It is vitally important to evaluate costs, benefits and risks associated with adopting a new method or technology prior to field implementation. The present research proposes a framework for estimating potential cost savings by implementing new method or technology in the field in terms of: (1) productivity-dependent crew cost; (2) time-dependent indirect cost; and (3) time-independent indirect cost in the current practice that can be removed. In regards to system reliability, the proposed framework guides the identification of possible breakdown event categories and the evaluation of probabilities and consequences for each category of event. A case study is presented in the context of developing an innovative TBM guidance automation system in tunnel construction. Potential cost saving resulting from implementing the new automation system for a 1,000-meter-long drainage tunnel project in Edmonton, Alberta is estimated to be $346k, which far outweighs the additional cost associated with system reliability (about $ 34k) by about ten-fold.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.409
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.005
GPT teacher head0.213
Teacher spread0.208 · 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