SHM data interpretation and structural condition assessment of the Manitoba Golden Boy
Bibliographic record
Abstract
The Golden Boy statue was placed on top of the Manitoba Legislative Building in 1919 and has since served as a source of inspiration to all Manitobans. An inspection of this heritage structure was conducted in 2001and revealed that its steel supporting shaft had deteriorated significantly. A decision was made to take the statue down for restoration. A stronger, stainless steel shaft replaced the worn shaft and sensors including electrical strain gauges, accelerometers, fiber optic sensors and thermocouples were installed. Also, a web camera and wind meter were installed on the roof of the building. Data from the sensors and video feed from the web camera are available through the Internet to facilitate web-based Structural Health Monitoring (SHM) in real-time. The support shaft of the statue can be idealized as a single degree of freedom cantilever structure. Wind and acceleration data are used to estimate the strains experienced by the shaft near the base, which are then correlated with the actual strain recorded by the strain sensors. This correlation was difficult as the data contained various levels of measurement errors or noise, and the strain data must be isolated from the thermal strain. Finally, the observed strain was correlated with hourly peak wind velocities reported by Environment Canada and an empirical relationship between these quantities was established to obtain an estimate of the strain in the shaft based on wind velocity, which will detect malfunctions in the sensors or deterioration of the structure. The study provided an understanding of the statue's behavior under a range of wind speeds and confidence in the SHM system for continuous and long term monitoring. It established a baseline response and alternative methods for predicting the behavior of the statue that provide a foundation for comparison with future stages in the Structural Health Monitoring of the Golden Boy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".