Trends on Integrity Management Programs (IMP) and Management Systems (MS) Audit and Incident Findings
Bibliographic record
Abstract
Over the past 12 years, as directed by federal and provincial regulations, Canadian pipeline companies have been formally developing and implementing Integrity Management Programs (IMPs). Since 1999, IMPs have been a requirement in the Canadian consensus industry standard CSA Z662. Furthermore, since the release of CSA Z662 Annex N in 2005, both the BC OGC and the Alberta Energy Resources Conservation Board (ERCB) (Canadian provincial regulators) have made CSA Z662 Annex N mandatory for their regulated companies. Annex N incorporates key management system (MS) elements such as a company’s policy and commitment, responsibilities, competency, planning, management of change, review and evaluation. This paper presents the findings of IMP audits conducted by the NEB and BC OGC regulators during the period of 2001–2011. This paper also includes the findings of NEB’s analysis of pipeline incidents that occurred between 2005 and 2009 and how these incident findings correlate to the audit findings. This paper is structured as follows: • Integrity management regulatory frameworks • IMP and MS elements and their interconnection • Audit findings from the NEB and the BC OGC • Incident findings from the NEB • Analysis of the audit findings and their correlation to incidents • Trends on IMP and MS audit and incident findings The paper provides a general understanding of the findings and their trends on pipeline integrity management and on incidents in terms of IMP/MS elements as described in Table 1. The results from this study may help stakeholders to determine strategies to increase the adequacy, implementation and effectiveness of pipeline integrity management. This paper does not include any company-specific information nor results and conclusions from any particular audit report or incident.
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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 | 0.018 | 0.096 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.011 | 0.022 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".