Deer Mountain Case Study: Integration of Pipe and Ground Monitoring Data With Historical Information to Develop a Landslide Management Plan
Bibliographic record
Abstract
Abstract Deer Mountain is an active landslide complex near Swan Hills, AB. Pembina owns two pipelines that traverse the landslide. Prior to abandonment, four leaks occurred on the NPS 8 pipeline due to interaction of circumferential stress corrosion cracking and ground movement. The NPS 10 pipeline is operating and has not leaked, but has previously been strain relieved in several locations. To develop and execute a geohazard management plan for the operating pipeline, Pembina integrated pipe and ground monitoring data with historical information into a geographic information system. Locations of bending strain areas, strain gauges, pipe wall assessment (PWA) anomalies, slope inclinometers, and piezometers were cross-referenced with previous leak sites, historical dig sites, historical strain reliefs, and areas of shallow pipe burial. Overlaying the PWA with pre-existing pipe data allowed for identification of segments with a higher density/magnitude of suspected soil to pipe interactions. Strain monitoring, strain relief, and a surface pipeline segment were prescribed. A detailed monitoring plan was also produced for the landslide complex. This case study presents the process of integrating data, specifying monitoring/mitigative measures, and implementing strain relief at four locations. Additionally, the paper will discuss the design of the surface pipeline segment.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".