Development of Virtual Laser Target Board for Tunnel Boring Machine Guidance Control
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.
Bibliographic record
Abstract
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.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it