Leak Detection Survey for a Large Diameter Water Transmission Main: City of Calgary
Bibliographic record
Abstract
In March of 2008 the City of Calgary Water Services Department contacted Pure Technologies for assistance in finding a leak in a water pipeline under a busy 4 lane road. Pure Technologies agreed to survey the line utilizing the SmartBall technology, an innovative leak detection technology for larger diameter water and waste water pipelines. The length of the survey was 2040 feet. The pipeline was a concrete pressure line 48 inches in diameter. The pipeline was installed in 1974. Within hours after the inspection the City of Calgary was notified of the location of the 34 gal/min leak. The location and approximate size of the leak was verified by City crews before repairs were made. The free-swimming acoustic leak detection tool demonstrated an ability to successfully identify and locate leaks in larger diameter transmission pipelines. The device was inserted into a fully operational pipeline. A 4 inch diameter access port was required for both insertion and retrieval of the device. Because the device traveled in the pressurized water column and passed directly adjacent to the leak, it clearly and distinctly identified the noise signature created by each leak. The position of the inspection tool was tracked by receivers from the surface - the position and location of the device known at all time. The recorded data allowed for correlation of any identified leak with the position of the device in the pipeline. This paper will summarize the field performance of the free swimming acoustic device utilized by the City of Calgary for the leak detection survey.
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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 | 0.001 | 0.002 |
| 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) | 0.002 | 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".