Bibliographic record
Abstract
Pipeline Research Council International Inc. (PRCI)'s Crack Management SRP has identified that circumferential cracking is a challenge for pipeline operating companies. The objective of PRCI NDE-4-24 was to create a framework to identify, assess and mitigate the risk due to circumferential cracking threats. Susceptibility to failure from circumferential cracking is linked to (1) circumfer-ential cracks subject to increasing axial or bending strains, or (2) growth in circumferential cracks at locations of residual strain. This project focusses on the first. No single in-line inspection (ILI) is capable of identifying circumferential cracks co-located within areas of increasing axial and bending strain. While bending strains are reliably detected with inertial mapping in-line inspection (ILI/IMU), identifying increasing strain due to subsidence or ground movement geotechnical requires separate expertise. Combining these into a framework to estimate the risk of a pipeline failure from circumferential cracks is the focus of this project. This report summarizes a methodology to develop a reliability criteria to evaluate risk for use in the PRCI NDE-4-24 circumferential crack framework. Once the risk for a given pipeline segment is estimated, the resulting values are compared to a reliability criteria to determine whether the risk is acceptable, or whether mitigating strategies must be initiated. As a result, a reliability criteria is an essential element to the framework and integrity program decision-making.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.124 | 0.067 |
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".