Watercourse Crossing Program: 10 Years Performance
Bibliographic record
Abstract
Abstract Plains Midstream Canada (PMC) completes a watercourse crossing program as part of its overall integrity management program. The approximately 9,900 kilometers of operating and discontinued pipelines are evaluated within the watercourse crossing program. The pipelines are located throughout the Canadian Provinces of Alberta, Saskatchewan, Manitoba and Ontario. The terrain traversed ranges from relatively steep near the Rocky Mountains to extremely flat in northern Alberta and Southern Ontario. Since 2008, PMC’s systematic watercourse crossing program has evolved and now consists of approximately 5,000 individual watercourse crossings. The bankfull width of the watercourses ranges from less than 1 m for intermittent streams to more than 700 m at major rivers. The watercourse crossing program is subjected to a continuous improvement process, with a focus on key learnings from pipeline failures, free spans and exposure. This paper describes the results from the program over the last 10 years and highlights program improvements. In addition, data from a failure and three free spans on the pipelines now owned by PMC, but where the exposure, free span or failure occurred prior to PMC purchasing the pipelines were added to expand the available data for the key learnings.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".