Validation of Photogrammetric Monitoring for TrenchlessConstruction Applications
Bibliographic record
Abstract
A primary concern of owners specifying trenchless installation and rehabilitation methods are surface movements during construction. Surface heave or settlement can occur as a result of contractor methodology, design, or geotechnical conditions. Performing quality assurance during and after construction provides owners with an understanding of what surface movements have occurred and if remedial action may be required. Traditional methods utilized to measure ground surface movements include surveying triangulation, geometric leveling, and global positioning system (GPS) surveying. This paper presents a procedure to utilize photogrammetry in the measuring of ground movements and examines its precision and accuracy in simulated field conditions. Utilizing consumer-grade digital single lens reflex (SLR) cameras, photogrammetry does not require highly trained personnel, takes less time, and costs less money than traditional methods. Accuracy is determined by comparing measurements taken with photogrammetry to those taken with traditional rod and level. The results are compiled and analyzed to determine the accuracy and precision of photogrammetry in measuring ground movements.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".