Quantitative Assessment of Incorrect Operations Threat
Bibliographic record
Abstract
Abstract Incorrect operations have risen to the second highest cause of incidents based on the Canadian Energy Regulator (CER) data from 2008 to September 2023 for incidents reported under the Onshore Pipeline Regulations and the Processing Plant Regulations. Despite its considerable impact on the performance of pipeline systems, a comprehensive understanding of what constitutes incorrect operations and the development of a robust risk assessment methodology for this specific threat remains limited. Incorrect operation is identified as a threat in the American Society of Mechanical Engineering standard, ASME B31.8S Managing System Integrity of Gas Pipelines, Appendix A-8, which defines it as a time-independent issue involving deviations from proper operating procedures or a failure to adhere to established protocols. The crux of this paper lies in the introduction of an innovative and comprehensive method tailored explicitly to evaluate the diverse failure modes associated with incorrect operations. The methodology advocates a systems-based approach by establishing correlations between failure incidents and an array of contributing factors, spanning system intricacies, job-specific attributes, and individual behavioral facets. The Pipeline and Hazardous Materials Safety Administration (PHMSA) database was leveraged to establish baseline failure frequencies specific to this threat. Additionally, incorporating data provided by a pipeline operator, the assessment of the incorrect operations threat was modified by considering factors such as construction year, temperature, state/province, high-consequence areas (HCA), maintenance, and asset type. The paper details the methodology employed in creating the model, and a preliminary evaluation of the model results is presented. Furthermore, the paper explores opportunities for further refinement of the model, discussing the “ideal” model and the data required for the ideal model to be realized. In doing so, the research aims to enhance our comprehension of incorrect operations within the complex context of pipelines, fostering advancements in risk assessment methodologies for improved pipeline safety and reliability.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".