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Record W1993560703 · doi:10.1061/9780784412343.0052

Development of Virtual Laser Target Board for Tunnel Boring Machine Guidance Control

2012· article· en· W1993560703 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInertial Sensor and Navigation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLine (geometry)LaserSimulationEngineeringComputer scienceField (mathematics)Head (geology)OpticsPhysics

Abstract

fetched live from OpenAlex

This research aims to develop a virtual laser target board methodology for tunnel boring machine (TBM) guidance control during tunneling operations. Current practice for TBM guidance using physical laser targets is evaluated. Coupled with a fully automated TBM tracking system resulted from in-house research, the virtual laser target board program is proposed to provide an effective aid for TBM operators and field managers in making critical decisions for tunnel alignment control. Comprehensive data processing procedures are carried out to determine: (1) TBM's position in the underground space, including any registered points on the TBM, e.g. center of TBM's cutter head; (2) tunneling progress; (3) line and grade deviations of the tunnel alignment; and (4) TBM's three-axis body rotations. Field experiments on a 2.4 m diameter TBM were conducted to collect registration data for on-line processing by the virtual laser target board program.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score0.279

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 head0.219
Teacher spread0.209 · 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

Quick stats

Citations7
Published2012
Admission routes1
Has abstractyes

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