Bibliographic record
Abstract
In this era of increased market competitiveness and the need for cost reduction strategies, natural gas pipeline and local distribution companies are now able to control the growth of their cathodic protection (CP) pipeline maintenance costs with the emergence of several new tools and related methods for diagnosing CP problems. In the early 1990’s, corrosion control engineers at the Southern California Gas Company (SoCal) were encouraged to find new methods to reduce maintenance costs associated with the company’s approximately 173 million feet of cathodically protected pipelines, mains and services. Mindful of how the maintenance problems in their CP systems were typically being resolved, an intriguing concept was conceived that could potentially reduce these costs and increase productivity by at least 40%. Driven to become more cost efficient, SoCal and the Pacific Gas and Electric Company (PG&E) in conjunction with the Gas Research Institute, now Gas Technology Institute (GTI) partnered with Radiodetection Corporation in the mid-90’s to research and design a more efficient way of troubleshooting and fault finding on CP systems. Radiodetections experience with electromagnetic detection equipment resulted in a family of non-invasive and cost-effective techniques to evaluate coating quality and to detect and record the flow of desired and interfering CP currents. The productivity gains and cost savings produced by this technology are significant. Additionally, problems that may have been difficult or impossible to detect now can be found allowing proactive and preventative maintenance. A history of these developments is discussed along with a brief review of the instruments technical aspects and capabilities. Typical field case studies are shown that demonstrate the improved corrosion control troubleshooting efficiencies available with these new technologies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".