Bibliographic record
Abstract
In the early 1920s, the National Bureau of Standards initiated a study into the underground corrosion of uncoated steel pipes. Very early in this study it became clear that coatings would be required for some environments, and a second study of coated pipes was initiated immediately. Pipeline coatings have been the subject of research and development ever since, and coatings, coating application methods, in-field application and repair technologies, and inspection technologies have evolved dramatically since these first studies. Today, a wide variety of high-quality coating systems are available for new pipeline construction, but the existing infrastructure of pipelines is protected with a wide range of coating types with varying ages. Therefore, the R&D needs of the pipeline community with respect to coatings ranges from testing protocols for evaluating new coatings and standards for quality control, to methods for evaluating of the performance and remaining life of coatings in service and remediation. The objective of this workshop was to bring the pipeline community together to discuss, identify, and prioritize coating R&D needs for improving the safety of pipelines.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".