Meeting the Geohazards Management Guidelines of Annex N
Bibliographic record
Abstract
The Canadian Standards Association’s Publication Z662-07, Annex N provides guidelines for pipeline integrity management programs. Government agencies that regulate pipelines in Alberta, British Columbia and other Canadian jurisdictions are increasingly using Annex N as the standard to which pipeline operators are held. This paper describes the experience of Pembina Pipeline Corporation (Pembina) in implementing a geohazards management program to fulfill components of Annex N. Central to Pembina’s program is a ground-based inspection program that feeds a geohazards database designed to store geotechnical and hydrotechnical site information and provide relative rankings of geohazard sites across the pipeline network. This geohazard management program fulfills several aspects of the Annex, particularly: record keeping; hazard identification and assessment; risk assessment and reduction; program planning; inspections and monitoring; and mitigation. Pembina’s experience in growing their geohazard inventory from 65 known sites to over 1300 systematically inspected and catalogued sites in a span of approximately two years is discussed. Also presented are methods by which consultants and Pembina personnel contribute to the geohazard inspection program and geohazard inventory, and how the ground inspection observations trigger follow-up inspections, monitoring and mitigation activities.
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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 | 0.034 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.025 | 0.022 |
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".