The Importance of “Significant” SCC Data Reported to the National Energy Board: An Update
Bibliographic record
Abstract
The National Energy Board (NEB) held an Inquiry in 1995 to determine the extent of knowledge and occurrence of SCC on Canadian oil and gas pipelines. The Report of the Inquiry, which was published in December 1996, issued 27 recommendations to promote public safety by encouraging the sharing of information on the extent of SCC and methods for managing and mitigating it. A major recommendation of the Report stated “that the NEB requires companies to report immediately to the NEB any finding of “significant” SCC and any immediate mitigative actions taken...” The definition of “significant” SCC is based on the definition adopted by the Canadian Energy Pipeline Association (CEPA) at the time of the Inquiry. Subsequently the NEB has required companies to submit this information and has used it to monitor the extent of and management of “significant” SCC on their regulated pipelines. This paper examines trends identified from the over 500 “significant” SCC reports submitted to the NEB. The analysis examines trends associated with product shipped, coating type, pipe grade, year of manufacture and SCC location on the pipe. In addition the paper will highlight the length and depth of “significant” SCC features, their methods of detection and the mitigation steps used to reduce any threat posed by the SCC. From the information presented in the paper, companies and regulators should be able to compare their “significant” SCC findings with the NEB average and in so doing aid in the continued management of SCC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.029 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.019 | 0.024 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".